Tag: About

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A desirable personal character will improve your potential to attain dreams and entire hard duties. If you have got an effective social person, you may stand depended on and even exist sought after through other human beings. By following the policies of your lifestyle or religion, you will match in and be normal within the group.

You will approximately through having a good person. Your precise personal person will help you obtain tough dreams and duties. A positive social individual permits you to be depended on and well-known with the aid of others. Following the rules of your way of life or faith consequences in being capable of matching in and being commonplace inside the organization.

  • What is Agile Methodology?

    What is Agile Methodology?

    What do you Mean about Agile Methodology?


    First, know about What is Agile? Agile has been the buzzword in project management for about a decade, and with good reason. Agile is actually an umbrella term over several project management approaches that are characterized by their ability to allow project teams to respond to changing requirements and priorities by using incremental work packages. While all agile methods have common characteristics, each agile method has unique processes that set it apart. Let’s look at how each method is used with Charlie’s team, who is developing a new software game. What is Agile Methodology? 

    Agile software development methodology is a process for developing software (like other software development methodologies Waterfall model, V-Model, Iterative model etc.) However, Agile methodology differs significantly from other methodologies. In English, Agile means ‘ability to move quickly and easily’ and responding swiftly to change – this is a key aspect of Agile software development as well.

    Agile-Methodology-process

    “Agile Development” is an umbrella term for several iterative and incremental software development methodologies. The most popular agile methodologies include Extreme Programming (XP), Scrum, Crystal, Dynamic Systems Development Method (DSDM), Lean Development, and Feature-Driven Development (FDD). Learning Development and Exercise of Self-Efficacy Over the Lifespan!

    Engineering methodologies required a lot of documentation thereby causing the pace of development to slow down considerably. Agile Methodologies evolved in the 1990s to significantly eliminate this bureaucratic nature of engineering methodology. It was part of developer’s reaction against “heavyweight” methods, who desired to drift away from traditional structured, bureaucratic approaches to software development and move towards more flexible development styles. They were called the ‘Agile’ or ‘Light Weight’ methods and were defined in 1974 by Edmonds in a research paper.

    An agile methodology is an approach to project management, typically used in software development. It refers to a group of software development methodologies based on iterative development. Requirements and solutions evolve through cooperation between self-organizing cross-functional teams, without concern for any hierarchy or team member roles. It promotes teamwork, collaboration, and process adaptability throughout the project life-cycle with increased face-to-face communication and a reduced amount of written documentation.

    Agile methods break tasks into small increments with no direct long-term planning. Every aspect of development is continually revisited throughout the lifecycle of a project by way of iterations (also called sprints). Iterations are short time frames (“timeboxes”) that normally last 1-4 weeks. This “inspect-and-adapt” approach significantly reduces both development costs and time to market. Each iteration involves working through a complete software development cycle characterized by planning, requirements analysis, design, coding, unit testing, and acceptance testing. This helps minimize overall risk and quicker project adaptability. While iteration may not have enough functionality necessary for a market release, the aim is to be ready for a release (with minimal bugs) at the end of each iteration.

    Typically, the team size is small (5-9 people) to enable easier communication and collaboration. Multiple teams may be required for larger developmental efforts which may also require a coordination of priorities across teams. Agile methods emphasize more face-to-face communication than written documents when the team is in the same location. However, when a team works at different locations, daily contact is maintained through video conferencing, e-mail, etc. The progress made in terms of the work done today, work scheduled for tomorrow and the possible roadblocks are discussed among the team members in brief sessions at the end of each working day. Besides, agile developmental efforts are supervised by a customer representative to ensure alignment between customer needs and company goals. New Roles of Human Resource Management in Business Development.

    Software Development was initially based on coding and fixing. That worked well for smaller software, but as the size and complexities of software grew a need for a proper process was felt because the debugging and testing of such software became extremely difficult. This gave birth to the Engineering Methodologies. The methodologies became highly successful since it structured the software development process. One of the most popular models that emerged was the Software Development Life Cycle (SDLC) that developed information systems in a very methodical manner.Waterfall method is one of the most popular examples of Engineering or the SDLC methodology. A paper published by Winston Royce in 1970 introduced it as an idea. It was derived from the hardware manufacture and construction strategies that were in practice during the 1970s. The relationship of each stage to the others can be roughly described as a waterfall, where the outputs from a specific stage serve as the initial inputs for the following stage. During each stage, additional information is gathered or developed, combined with the inputs, and used to produce the stage deliverables. It is important to note that the additional information is restricted in scope; “new ideas” that would take the project in directions not anticipated by the initial set of high-level requirements are not incorporated into the project. Rather, ideas for new capabilities or features that are out-of-scope are preserved for later consideration.

    What-is-Agile-Methodology


  • Knowledge Management Systems

    Knowledge Management Systems

    Definition and Meaning of KMS (Knowledge Management Systems); A method for the improvement of business process performance. A knowledge management system is most often uses in business in applications such as information systems, business administration, computer science, public policy, and general management. Common company departments for knowledge management systems include human resources, business strategy, and information technology.

    Here is the article to explain, What is KMS Knowledge Management Systems? Definition and Meaning

    Every organization aims to achieve its set goals and objectives as well as secure a competitive advantage over its competitors. However, these cannot achieve or actualized if staff or workers act independently and do not share ideas. Today, prominent businesses are becoming more aware that the knowledge of their employees is one of their primary assets. Sometimes organizational decisions cannot be effectively made with information alone; there is a need for knowledge application. An effective knowledge management system can give a company the competitive edge it needs to be successful, and, for that reason, knowledge management projects should be a high priority.

    Development;

    Knowledge Management Systems (KMS) “developed to support and enhance the organizational knowledge processes of knowledge creation, storage, retrieval, transfer, and application (Alavi & Leidner, 2001) This means that for any organization to be competitive in today’s global world there is a need for combination or pooling together of ideas by employees to achieve teamwork; this is in support of the saying that ‘two good heads are better than one. Since organizational knowledge is one of the important assets of the organization; it needs to manage like other assets, hence the need for what is Knowledge Management Systems (KMS).

    Knowledge management systems ‘collect all relevant knowledge and experience in the firm; and, make it available whenever and wherever it needs to support business processes and management decisions. Knowledge here could refer to as the understanding that a person has gained through education, experience, discovery, intuition, and insight or a combination of instincts, ideas, rules, and procedures that guide actions and decisions. It is an intangible asset that is unique and can use to achieve long-term strategic benefits or advantages. This is because knowledge has more competitive significance than physical assets in a consulting organization like ours that relies on unique competencies and methods. Also, unlike other physical assets of an organization, knowledge is not subject to the law of diminishing returns as are physical assets, but increases in value as people share it.

    Understand;

    Knowledge can in a form that can state, codified or written, and understandable by everyone (explicit) or in a form that cannot express easily and unconsciously applied but understood by individuals (implicit or tacit). Therefore, what knowledge management systems do is to provide collaborative capabilities; using groupware to facilitate sharing of explicit and implicit knowledge among employees. It also means to change people’s behavior to make their experience and expertise available to others. These systems involve a process that helps organizations identify, select, organize, disseminate and transfer important information; and expertise that is part of the organizational memory that typically resides within the organization in an unstructured manner. Learn more about;

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    Objetives;

    The main objective of knowledge management systems is to identify knowledge; and, explicate it in a way that it can share formally, and thus re-used. It helps in transferring the intellectual assets of the firm to value processes such as innovation and knowledge acquisition. It means improving the organization’s ability to execute its core processes more efficiently by capturing intellectual assets for the tangible benefit of the organization. Knowledge Management Systems also aim at codifying knowledge (such as best practices); organizing it in repositories for later access, finding knowledge (using search engines and other schemes); and providing organized ways to find people who possess the required knowledge.

    It poises towards determining what knowledge the organization has, as well as acquiring the knowledge that is lacking to provide collaborative capabilities and facilitate sharing of explicit and implicit knowledge among employees. Knowledge management systems enhance knowledge creation through learning, knowledge sharing, and communication; through collaboration as well as knowledge capture and explication, use and reuse, access, and archiving. It means transforming information and intellectual assets into enduring value for the organization; and, transforming knowledge to add value to the process and operations of the business. It also aims at leveraging knowledge strategically to business to accelerate growth; and innovation as well as using knowledge to provide a competitive advantage for the business.

    Problems and Solve;

    These systems also capture knowledge about how problems can solve to promote organizational learning, leading to further knowledge creation. In doing this, intellects that are in the form of tacit knowledge in individuals, groups within the organization; and other areas transfer to value processes that lead to innovation, knowledge creation, and replenishment of the organization’s core values. Knowledge management systems also capture knowledge in an external repository, identify needed knowledge and help in matching and exchanging knowledge. Some technologies that support this system are e-mail, document management, search engines, enterprise information portal, data warehouse, groupware, workflow management, and web-based training. Knowledge management systems also mean to provide collaborative capabilities, using groupware to facilitate sharing of explicit knowledge among employees; its activities or processes are supported by software such as Wincite, Grapevine, and Knowledge X.

  • What is RFID (Radio Frequency Identification)? Meaning and Definition!

    What is RFID (Radio Frequency Identification)? Meaning and Definition!

    Learn, RFID (Radio Frequency Identification), Meaning and Definition!


    Radio Frequency Identification (RFID) In past few recent years, the automatic identification techniques have become quite more than popular and they have also find their places into the core of service industries, manufacturing companies, aviation, clothing, transport systems and much more. And, it’s pretty clear by this point of time that the automated identification technology especially RFID, is highly helpful in providing information regarding the timings, location and even more intense information about people, animals, goods etc. in transit. RFID is responsible for storage of large amount of data and is reprogrammable also as in contrast with its counterpart barcodes automatic identification technology.

    #Meaning of RFID!

    “Radio-frequency identification (RFID) uses electromagnetic fields to automatically identify and track tags attached to objects. The tags contain electronically stored information. Passive tags collect energy from a nearby RFID reader’s interrogating radio waves. Active tags have a local power source such as a battery and may operate at hundreds of meters from the RFID reader. Unlike a barcode, the tag need not be within the line of sight of the reader, so it may be embedded in the tracked object. RFID is one method for Automatic Identification and Data Capture (AIDC).”

    In everyday life, the most common form of an electronic data-carrying device if often a smartcard which is probably based upon the contact field. But, this kind of a contact oriented card is normally impractical and less flexible to use. On the contrary, if we think of a contactless card with contactless data transferring capabilities, it would be far more flexible. This communication happens between the data carrying device and its reader. Now, this situation may further appear as ideal if it so happens that the power for the data carrying device comes from the reader by making use of the contactless technology. Because of this specific kind of power transferring and data carrying procedures, the contactless automatic identification systems are termed as Radio frequency Identification Systems.

    What is Radio Frequency Identification (RFID)?

    Definition: The term RFID stands for Radio Frequency Identification. Radio stands for invocation of the wireless transmission and propagation of information or data. For operating RFID devices, Frequency defines spectrum, may it be low, high, ultra high and microwave, each with distinguishing characteristics. Identification relates to identify the items with the help of various codes present in a data carrier (memory-based) and available via radio frequency reading. The RFID is a term which is used for any device that can be sensed or detected from a distance with few problems of obstruction. The invention of RFID term lies in the origin of tags that reflect or retransmit a radio-frequency signal. RFID makes use of radio frequencies to communicate between two of its components namely RFID tag and the RFID reader. The RFID system can be broadly categorized according to the physical components of frequency and data.

    Physical components of the RFID system include, but are not limited to, the following: numerous RFID tags and RFID readers and Computers. The factors associated with the RFID tags are the kind of power source its has, the environment in which it operates, the antenna on the tag for communication with the reader, its corresponding standard, memory, logic applied on the chip and application methods on the tag. The RFID tag refers to a tiny radio device also known as radio barcode, transponder or smart label. This tag is comprised of a simple silicon microchip which is attached to a small flat antenna and mounted on a substrate.

    The entire device can then be encapsulated in various materials dependent upon its intended usage. The finished RFID tag can then be attached to an object, typically an item, box or pallet. This tag can then be read remotely to ascertain position, identity or state of an item. The application methods of an RFID tag may take the forms attached, removable, embedded or conveyed. Further, the RFID tags depend upon the power source which may be a battery in case of active-tags and an RFID reader in case of passive tags. In context of the environment in which the tag operates, the role of temperature range and the humidity range comes into picture.

    The RFID reader is also referred as interrogator or scanner. Its purpose is to send and receive RF data from tags. The RFID reader factors include its antenna, polarization, protocol, interface and portability. The antenna for communication in case of the RFID reader may be internal or external and its ports may assume the values single or multiple. The polarization in case of an RFID reader may be linear or circular and single or multiple protocols may be used. In an RFID reader, Ethernet, serial, Wi-Fi, USB or other interfaces may be used. Regarding portability associated with the reader, it may be fixed or handheld.

    Apart from the RFID tags and readers, host computers are also amongst the part of the physical components of an RFID system. The data acquired by the RFID readers is passed to the host computer which may further run a specialist RFID software, or middleware to filter the data and route it to the correct application to be processed into useful information.

    Apart from the physical components of an RFID system, the RFID system may be perceived from the frequency perspective. In RFID systems, the frequency may further be classified according to the signal distance, signal range, reader to tag, tag to reader and coupling. The signal distance includes the read range and the write range. The signal range here in case of RFID systems reflects the various frequency bands i.e. LF, HF, UHF and Microwave. Further, the reader to tag frequency may assume single frequency or multiple frequencies. In case of tag to reader frequency, it may be subharmonic, harmonic or an harmonic.

    The data sub classification in RFID systems includes, the security associated with the RFID systems, multi-tag read co-ordination and processing. In the similar context, public algorithm, proprietary algorithm or none are applied for the security associated with the RFID systems. The multi-tag read co-ordination techniques used in the latest RFID systems include SDMA, TDMA, FDMA and CDMA. The processing part is composed of the middleware which further has its own architecture which may assume a single or multi-tier shape and its associated location may be reader or the server.

    Basic Information: RFID tags are used in many industries, for example, an RFID tag attached to an automobile during production can be used to track its progress through the assembly line; RFID-tagged pharmaceuticals can be tracked through warehouses; and implanting RFID microchips in livestock and pets allows for positive identification of animals.

    Since RFID tags can be attached to cash, clothing, and possessions, or implanted in animals and people, the possibility of reading personally-linked information without consent has raised serious privacy concerns. These concerns resulted in standard specifications development addressing privacy and security issues. ISO/IEC 18000 and ISO/IEC 29167 use on-chip cryptography methods for untraceability, tag and reader authentication, and over-the-air privacy. ISO/IEC 20248 specifies a digital signature data structure for RFID and barcodes providing data, source and read method authenticity. This work is done within ISO/IEC JTC 1/SC 31 Automatic identification and data capture techniques.

    In 2014, the world RFID market is worth US$8.89 billion, up from US$7.77 billion in 2013 and US$6.96 billion in 2012. This includes tags, readers, and software/services for RFID cards, labels, fobs, and all other form factors. The market value is expected to rise to US$18.68 billion by 2026.

    What is RFID Radio Frequency Identification Meaning and Definition - ilearnlot


  • What is Phases of the Data Mining Process?

    What is Phases of the Data Mining Process?

    What is Phases of the Data Mining Process?


    The Cross-Industry Standard Process for Data Mining (CRISP-DM) is the dominant data-mining process framework. It’s an open standard; anyone may use it. The following list describes the various phases of the process.

    Phases-of-the-Data-Mining-Process
    The Cross-Industry Standard Process for Data Mining

    Business understanding

    In the business understanding phase:

    First, it is required to understand business objectives clearly and find out what are the business’s needs.

    Next, we have to assess the current situation by finding of the resources, assumptions, constraints and other important factors which should be considered.

    Then, from the business objectives and current situations, we need to create data mining goals to achieve the business objectives within the current situation.

    Finally, a good data mining plan has to be established to achieve both business and data mining goals. The plan should be as detailed as possible.

    Data understanding

    First, the data understanding phase starts with initial data collection, which we collect from available data sources, to help us get familiar with the data. Some important activities must be performed including data load and data integration in order to make the data collection successfully.

    Next, the “gross” or “surface” properties of acquired data need to be examined carefully and reported.

    Then, the data needs to be explored by tackling the data mining questions, which can be addressed using querying, reporting, and visualization.

    Finally, the data quality must be examined by answering some important questions such as “Is the acquired data complete?”, “Is there any missing values in the acquired data?”

    Data preparation

    The data preparation typically consumes about 90% of the time of the project. The outcome of the data preparation phase is the final data set. Once available data sources are identified, they need to be selected, cleaned, constructed and formatted into the desired form. The data exploration task at a greater depth may be carried during this phase to notice the patterns based on business understanding.

    Modeling

    First, modeling techniques have to be selected to be used for the prepared dataset.

    Next, the test scenario must be generated to validate the quality and validity of the model.

    Then, one or more models are created by running the modeling tool on the prepared dataset.

    Finally, models need to be assessed carefully involving stakeholders to make sure that created models are met business initiatives.

    Evaluation

    In the evaluation phase, the model results must be evaluated in the context of business objectives in the first phase. In this phase, new business requirements may be raised due to the new patterns that have been discovered in the model results or from other factors. Gaining business understanding is an iterative process in data mining. The go or no-go decision must be made in this step to move to the deployment phase.

    Deployment

    The knowledge or information, which we gain through data mining process, needs to be presented in such a way that stakeholders can use it when they want it. Based on the business requirements, the deployment phase could be as simple as creating a report or as complex as a repeatable data mining process across the organization. In the deployment phase, the plans for deployment, maintenance, and monitoring have to be created for implementation and also future supports. From the project point of view, the final report of the project needs to summary the project experiences and review the project to see what need to improved created learned lessons.

    The CRISP-DM offers a uniform framework for experience documentation and guidelines. In addition, the CRISP-DM can apply in various industries with different types of data.

    In this article, you have learned about the data mining processes and examined the cross-industry standard process for data mining.

    Something is not Forgetting What? Data mining is a promising and relatively new technology. Data mining is defined as a process of discovering hidden valuable knowledge by analyzing large amounts of data, which is stored in databases or data warehouse, using various data mining techniques such as machine learning, artificial intelligence(AI) and statistical.

    Many organizations in various industries are taking advantages of data mining including manufacturing, marketing, chemical, aerospace… etc, to increase their business efficiency. Therefore, the needs for a standard data mining process increased dramatically. A data mining process must be reliable and it must be repeatable by business people with little or no knowledge of data mining background. As the result, in 1990, a cross-industry standard process for data mining (CRISP-DM) first published after going through a lot of workshops, and contributions from over 300 organizations.

    What-is-Phases-of-the-Data-Mining-Process


  • Process of The Data Mining

    Process of The Data Mining

    Process of The Data Mining


    Data mining is a promising and relatively new technology. Data mining is defined as a process of discovering hidden valuable knowledge by analyzing large amounts of data, which is stored in databases or data warehouse, using various data mining techniques such as machine learning, artificial intelligence(AI) and statistical.

    Many organizations in various industries are taking advantages of data mining including manufacturing, marketing, chemical, aerospace… etc, to increase their business efficiency. Therefore, the needs for a standard data mining process increased dramatically. A data mining process must be reliable and it must be repeatable by business people with little or no knowledge of data mining background. As the result, in 1990, a cross-industry standard process for data mining (CRISP-DM) first published after going through a lot of workshops, and contributions from over 300 organizations.

    The data mining process involves much hard work, including perhaps building data warehouse if the enterprise does not have one. A typical data mining process is likely to include the following steps:

    Requirements analysis: The enterprise decision makers need to formulate goals that the data mining process is expected to achieve. The business problem must be clearly defined. One cannot use data mining without a good idea of what kind of outcomes the enterprise is looking for, since the technique to be used and the data that is required are likely to be different for different goals. Furthermore, if the objectives have been clearly defined, it is easier to evaluate the results of the project. Once the goals have been agreed upon, the following further steps are needed.

    Data selection and collection: This step may include finding the best source databases for the data that is required. If the enterprise has implemented a data warehouse, then most of the data could be available there. If the data is not available in the warehouse or the enterprise does not have a warehouse, the source OLTP (On-line Transaction Processing) systems need to be identified and the required information extracted and stored in some temporary system. In some cases, only a sample of the data available may be required.

    Cleaning and preparing data: This may not be an onerous task if a data warehouse containing the required . data exists, since most of this must have already been done when data was loaded in the warehouse. Otherwise this task can be very resource intensive and sometimes more than 50% of effort in a data mining project is spent on this step. Essentially a data store that integrates data from a number of databases may need to be created. When integrating data, one often encounters problems like identifying data, dealing with missing data, data conflicts and ambiguity. An ETL (extraction, transformation and loading) tool may be used to overcome these problems.

    Data mining exploration and validation: Once appropriate data has been collected and cleaned, it is possible to start data mining exploration. Assuming that the user has access to one or more data mining tools, a data mining model may be constructed based on the enterprise’s needs. It may be possible to take a sample of data and apply a number of relevant techniques. For each technique the results should be evaluated and their significance interpreted. This is likely to be an iterative process which should lead to selection of one or more techniques that are suitable for further exploration, testing, and validation.

    Implementing, evaluating, and monitoring: Once a model has been selected and validated, the model can be implemented for use by the decision makers. This may involve software development for generating reports, or for results visualization and explanation for managers. It may be that more than one technique is available for the given data mining task. It is then important to evaluate the results and choose the best technique. Evaluation may involve checking the accuracy and effectiveness of the technique. Furthermore, there is a need for regular monitoring of the performance of the techniques that have been implemented. It is essential that use of the tools by the managers be monitored and results evaluated regularly. Every enterprise evolves with time and so must the data mining system. Therefore, monitoring is likely to lead from time to time to refinement of tools and techniques that have been implemented.

    Results visualization: Explaining the results of data mining to the decision makers is an important step of the data mining process. Most commercial data mining tools include data visualization modules. These tools are often vital in communicating the data mining results to the managers, although a problem dealing with a number of dimensions must be visualized using a two dimensional computer screen or printout. Clever data visualization tools are being developed to display results that deal with more than two dimensions. The visualization tools available should be tried and used if found effective for the given problem.

    Process-of-The-Data-Mining


  • What is Data Mining?

    What is Data Mining?

    What is Data Mining?


    Data mining involves the use of sophisticated data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. These tools can include statistical models, mathematical algorithms, and machine learning methods such as neural networks or decision trees. Consequently, data mining consists of more than collecting and managing data, it also includes analysis and prediction. The objective of data mining is to identify valid, novel, potentially useful, and understandable correlations and patterns in existing data. Finding useful patterns in data is known by different names (e.g., knowledge extraction, information discovery, information harvesting, data archaeology, and data pattern processing).

    The term “data mining” is primarily used by statisticians, database researchers, and the business communities. The term KDD (Knowledge Discovery in Databases) refers to the overall process of discovering useful knowledge from data, where data mining is a particular step in this process. The steps in the KDD process, such as data preparation, data selection, data cleaning, and proper interpretation of the results of the data mining process, ensure that useful knowledge is derived from the data. Data mining is an extension of traditional data analysis and statistical approaches as it incorporates analytical techniques drawn from various disciplines like AI, machine learning, OLAP, data visualization, etc.

    Data Mining covers variety of techniques to identify nuggets of information or decision-making knowledge in bodies of data, and extracting these in such a way that they can be. Put to use in the areas such as decision support, prediction, forecasting and estimation. The data is often voluminous, but as it stands of low value as no direct use can be made of it; it is the hidden information in the data that is really useful. Data mining encompasses a number of different technical approaches, such as clustering, data summarization, learning classification rules, finding dependency net works, analyzing changes, and detecting anomalies. Data mining is the analysis of data and the use of software techniques for finding patterns and regularities in sets of data. The computer is responsible for finding the patterns by identifying the underlying rules and features in the data. It is possible to ‘strike gold’ in unexpected places as the data mining software extracts patterns not previously discernible or so obvious that no-one has noticed them before. In Data Mining, large volumes of data are sifted in an attempt to find something worthwhile.

    Data mining plays a leading role in the every facet of Business. It is one of the ways by which a company can gain competitive advantage. Through application of Data mining, one can tum large volumes of data collected from various front-end systems like Transaction Processing Systems, ERP, and operational CRM into meaningful knowledge.

    “Data mining is the computing process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. Data mining is the analysis step of the “knowledge discovery in databases” process, or KDD.”

    Data Mining History and Current Advances

    The process of digging through data to discover hidden connections and predict future trends has a long history. Sometimes referred to as “knowledge discovery in databases,” the term “data mining” wasn’t coined until the 1990s. But its foundation comprises three intertwined scientific disciplines: statistics (the numeric study of data relationships), artificial intelligence (human-like intelligence displayed by software and/or machines) and machine learning (algorithms that can learn from data to make predictions). What was old is new again, as data mining technology keeps evolving to keep pace with the limitless potential of big data and affordable computing power.

    Over the last decade, advances in processing power and speed have enabled us to move beyond manual, tedious and time-consuming practices to quick, easy and automated data analysis. The more complex the data sets collected, the more potential there is to uncover relevant insights. Retailers, banks, manufacturers, telecommunications providers and insurers, among others, are using data mining to discover relationships among everything from pricing, promotions and demographics to how the economy, risk, competition and social media are affecting their business models, revenues, operations and customer relationships.

    Who’s using it?

    Data mining is at the heart of analytics efforts across a variety of industries and disciplines.

    Communications: In an overloaded market where competition is tight, the answers are often within your consumer data. Multimedia and telecommunications companies can use analytic models to make sense of mountains of customers data, helping them predict customer behavior and offer highly targeted and relevant campaigns.

    Insurance: With analytic know-how, insurance companies can solve complex problems concerning fraud, compliance, risk management and customer attrition. Companies have used data mining techniques to price products more effectively across business lines and find new ways to offer competitive products to their existing customer base.

    Education: With unified, data-driven views of student progress, educators can predict student performance before they set foot in the classroom – and develop intervention strategies to keep them on course. Data mining helps educators access student data, predict achievement levels and pinpoint students or groups of students in need of extra attention.

    Manufacturing: Aligning supply plans with demand forecasts is essential, as is early detection of problems, quality assurance and investment in brand equity. Manufacturers can predict wear of production assets and anticipate maintenance, which can maximize uptime and keep the production line on schedule.

    Banking: Automated algorithms help banks understand their customer base as well as the billions of transactions at the heart of the financial system. Data mining helps financial services companies get a better view of market risks, detect fraud faster, manage regulatory compliance obligations and get optimal returns on their marketing investments.

    Retail: Large customer databases hold hidden insights that can help you improve customer relationships, optimize marketing campaigns and forecast sales. Through more accurate data models, retail companies can offer more targeted campaigns – and find the offer that makes the biggest impact on the customer.

    What-is-Data-Mining


  • About Love

    About Love

    About Love


    Dear Learner, The Short Story by Anton Chekhov

    AT lunch next day there were very nice pies, crayfish, and mutton cutlets; and while we were eating, Nikanor, the cook, came up to ask what the visitors would like for dinner. He was a man of medium height, with a puffy face and little eyes; he was close-shaven, and it looked as though his moustaches had not been shaved, but had been pulled out by the roots. Alehin told us that the beautiful Pelagea was in love with this cook. As he drank and was of a violent character, she did not want to marry him, but was willing to live with him without. He was very devout, and his religious convictions would not allow him to “live in sin”; he insisted on her marrying him, and would consent to nothing else, and when he was drunk he used to abuse her and even beat her. Whenever he got drunk she used to hide upstairs and sob, and on such occasions Alehin and the servants stayed in the house to be ready to defend her in case of necessity.

    We began talking about love.

    “How love is born,” said Alehin, “why Pelagea does not love somebody more like herself in her spiritual and external qualities, and why she fell in love with Nikanor, that ugly snout — we all call him ‘The Snout’ — how far questions of personal happiness are of consequence in love — all that is known; one can take what view one likes of it. So far only one incontestable truth has been uttered about love: ‘This is a great mystery.’ Everything else that has been written or said about love is not a conclusion, but only a statement of questions which have remained unanswered. The explanation which would seem to fit one case does not apply in a dozen others, and the very best thing, to my mind, would be to explain every case individually without attempting to generalize. We ought, as the doctors say, to individualize each case.”

    “Perfectly true,” Burkin assented.

    “We Russians of the educated class have a partiality for these questions that remain unanswered. Love is usually poeticized, decorated with roses, nightingales; we Russians decorate our loves with these momentous questions, and select the most uninteresting of them, too. In Moscow, when I was a student, I had a friend who shared my life, a charming lady, and every time I took her in my arms she was thinking what I would allow her a month for housekeeping and what was the price of beef a pound. In the same way, when we are in love we are never tired of asking ourselves questions: whether it is honourable or dishonourable, sensible or stupid, what this love is leading up to, and so on. Whether it is a good thing or not I don’t know, but that it is in the way, unsatisfactory, and irritating, I do know.”

    It looked as though he wanted to tell some story. People who lead a solitary existence always have something in their hearts which they are eager to talk about. In town bachelors visit the baths and the restaurants on purpose to talk, and sometimes tell the most interesting things to bath attendants and waiters; in the country, as a rule, they unbosom themselves to their guests. Now from the window we could see a grey sky, trees drenched in the rain; in such weather we could go nowhere, and there was nothing for us to do but to tell stories and to listen.

    “I have lived at Sofino and been farming for a long time,” Alehin began, “ever since I left the University. I am an idle gentleman by education, a studious person by disposition; but there was a big debt owing on the estate when I came here, and as my father was in debt partly because he had spent so much on my education, I resolved not to go away, but to work till I paid off the debt. I made up my mind to this and set to work, not, I must confess, without some repugnance. The land here does not yield much, and if one is not to farm at a loss one must employ serf labour or hired labourers, which is almost the same thing, or put it on a peasant footing — that is, work the fields oneself and with one’s family. There is no middle path. But in those days I did not go into such subtleties. I did not leave a clod of earth unturned; I gathered together all the peasants, men and women, from the neighbouring villages; the work went on at a tremendous pace. I myself ploughed and sowed and reaped, and was bored doing it, and frowned with disgust, like a village cat driven by hunger to eat cucumbers in the kitchen-garden. My body ached, and I slept as I walked. At first it seemed to me that I could easily reconcile this life of toil with my cultured habits; to do so, I thought, all that is necessary is to maintain a certain external order in life. I established myself upstairs here in the best rooms, and ordered them to bring me there coffee and liquor after lunch and dinner, and when I went to bed I read every night the Yyesnik Evropi. But one day our priest, Father Ivan, came and drank up all my liquor at one sitting; and the Yyesnik Evropi went to the priest’s daughters; as in the summer, especially at the haymaking, I did not succeed in getting to my bed at all, and slept in the sledge in the barn, or somewhere in the forester’s lodge, what chance was there of reading? Little by little I moved downstairs, began dining in the servants’ kitchen, and of my former luxury nothing is left but the servants who were in my father’s service, and whom it would be painful to turn away.

    “In the first years I was elected here an honourary justice of the peace. I used to have to go to the town and take part in the sessions of the congress and of the circuit court, and this was a pleasant change for me. When you live here for two or three months without a break, especially in the winter, you begin at last to pine for a black coat. And in the circuit court there were frock-coats, and uniforms, and dress-coats, too, all lawyers, men who have received a general education; I had some one to talk to. After sleeping in the sledge and dining in the kitchen, to sit in an arm-chair in clean linen, in thin boots, with a chain on one’s waistcoat, is such luxury!

    “I received a warm welcome in the town. I made friends eagerly. And of all my acquaintanceships the most intimate and, to tell the truth, the most agreeable to me was my acquaintance with Luganovitch, the vice-president of the circuit court. You both know him: a most charming personality. It all happened just after a celebrated case of incendiarism; the preliminary investigation lasted two days; we were exhausted. Luganovitch looked at me and said:

    ” ‘Look here, come round to dinner with me.’

    “This was unexpected, as I knew Luganovitch very little, only officially, and I had never been to his house. I only just went to my hotel room to change and went off to dinner. And here it was my lot to meet Anna Alexyevna, Luganovitch’s wife. At that time she was still very young, not more than twenty-two, and her first baby had been born just six months before. It is all a thing of the past; and now I should find it difficult to define what there was so exceptional in her, what it was in her attracted me so much; at the time, at dinner, it was all perfectly clear to me. I saw a lovely young, good, intelligent, fascinating woman, such as I had never met before; and I felt her at once some one close and already familiar, as though that face, those cordial, intelligent eyes, I had seen somewhere in my childhood, in the album which lay on my mother’s chest of drawers.

    “Four Jews were charged with being incendiaries, were regarded as a gang of robbers, and, to my mind, quite groundlessly. At dinner I was very much excited, I was uncomfortable, and I don’t know what I said, but Anna Alexyevna kept shaking her head and saying to her husband:

    ” ‘Dmitry, how is this?’

    “Luganovitch is a good-natured man, one of those simple-hearted people who firmly maintain the opinion that once a man is charged before a court he is guilty, and to express doubt of the correctness of a sentence cannot be done except in legal form on paper, and not at dinner and in private conversation.

    ” ‘You and I did not set fire to the place,’ he said softly, ‘and you see we are not condemned, and not in prison.’

    “And both husband and wife tried to make me eat and drink as much as possible. From some trifling details, from the way they made the coffee together, for instance, and from the way they understood each other at half a word, I could gather that they lived in harmony and comfort, and that they were glad of a visitor. After dinner they played a duet on the piano; then it got dark, and I went home. That was at the beginning of spring.

    “After that I spent the whole summer at Sofino without a break, and I had no time to think of the town, either, but the memory of the graceful fair-haired woman remained in my mind all those days; I did not think of her, but it was as though her light shadow were lying on my heart.

    “In the late autumn there was a theatrical performance for some charitable object in the town. I went into the governor’s box (I was invited to go there in the interval); I looked, and there was Anna Alexyevna sitting beside the governor’s wife; and again the same irresistible, thrilling impression of beauty and sweet, caressing eyes, and again the same feeling of nearness. We sat side by side, then went to the foyer.

    ” ‘You’ve grown thinner,’ she said; ‘have you been ill?’

    ” ‘Yes, I’ve had rheumatism in my shoulder, and in rainy weather I can’t sleep.’

    ” ‘You look dispirited. In the spring, when you came to dinner, you were younger, more confident. You were full of eagerness, and talked a great deal then; you were very interesting, and I really must confess I was a little carried away by you. For some reason you often came back to my memory during the summer, and when I was getting ready for the theatre today I thought I should see you.’

    “And she laughed.

    ” ‘But you look dispirited today,’ she repeated; ‘it makes you seem older.’

    “The next day I lunched at the Luganovitchs’. After lunch they drove out to their summer villa, in order to make arrangements there for the winter, and I went with them. I returned with them to the town, and at midnight drank tea with them in quiet domestic surroundings, while the fire glowed, and the young mother kept going to see if her baby girl was asleep. And after that, every time I went to town I never failed to visit the Luganovitchs. They grew used to me, and I grew used to them. As a rule I went in unannounced, as though I were one of the family.

    ” ‘Who is there?’ I would hear from a faraway room, in the drawling voice that seemed to me so lovely.

    ” ‘It is Pavel Konstantinovitch,’ answered the maid or the nurse.

    “Anna Alexyevna would come out to me with an anxious face, and would ask every time:

    ” ‘Why is it so long since you have been? Has anything happened?’

    “Her eyes, the elegant refined hand she gave me, her indoor dress, the way she did her hair, her voice, her step, always produced the same impression on me of something new and extraordinary in my life, and very important. We talked together for hours, were silent, thinking each our own thoughts, or she played for hours to me on the piano. If there were no one at home I stayed and waited, talked to the nurse, played with the child, or lay on the sofa in the study and read; and when Anna Alexyevna came back I met her in the hall, took all her parcels from her, and for some reason I carried those parcels every time with as much love, with as much solemnity, as a boy.

    “There is a proverb that if a peasant woman has no troubles she will buy a pig. The Luganovitchs had no troubles, so they made friends with me. If I did not come to the town I must be ill or something must have happened to me, and both of them were extremely anxious. They were worried that I, an educated man with a knowledge of languages, should, instead of devoting myself to science or literary work, live in the country, rush round like a squirrel in a rage, work hard with never a penny to show for it. They fancied that I was unhappy, and that I only talked, laughed, and ate to conceal my sufferings, and even at cheerful moments when I felt happy I was aware of their searching eyes fixed upon me. They were particularly touching when I really was depressed, when I was being worried by some creditor or had not money enough to pay interest on the proper day. The two of them, husband and wife, would whisper together at the window; then he would come to me and say with a grave face:

    ” ‘If you really are in need of money at the moment, Pavel Konstantinovitch, my wife and I beg you not to hesitate to borrow from us.’

    “And he would blush to his ears with emotion. And it would happen that, after whispering in the same way at the window, he would come up to me, with red ears, and say:

    ” ‘My wife and I earnestly beg you to accept this present.’

    “And he would give me studs, a cigar-case, or a lamp, and I would send them game, butter, and flowers from the country. They both, by the way, had considerable means of their own. In early days I often borrowed money, and was not very particular about it — borrowed wherever I could — but nothing in the world would have induced me to borrow from the Luganovitchs. But why talk of it?

    “I was unhappy. At home, in the fields, in the barn, I thought of her; I tried to understand the mystery of a beautiful, intelligent young woman’s marrying some one so uninteresting, almost an old man (her husband was over forty), and having children by him; to understand the mystery of this uninteresting, good, simple-hearted man, who argued with such wearisome good sense, at balls and evening parties kept near the more solid people, looking listless and superfluous, with a submissive, uninterested expression, as though he had been brought there for sale, who yet believed in his right to be happy, to have children by her; and I kept trying to understand why she had met him first and not me, and why such a terrible mistake in our lives need have happened.

    “And when I went to the town I saw every time from her eyes that she was expecting me, and she would confess to me herself that she had had a peculiar feeling all that day and had guessed that I should come. We talked a long time, and were silent, yet we did not confess our love to each other, but timidly and jealously concealed it. We were afraid of everything that might reveal our secret to ourselves. I loved her tenderly, deeply, but I reflected and kept asking myself what our love could lead to if we had not the strength to fight against it. It seemed to be incredible that my gentle, sad love could all at once coarsely break up the even tenor of the life of her husband, her children, and all the household in which I was so loved and trusted. Would it be honourable? She would go away with me, but where? Where could I take her? It would have been a different matter if I had had a beautiful, interesting life — if, for instance, I had been struggling for the emancipation of my country, or had been a celebrated man of science, an artist or a painter; but as it was it would mean taking her from one everyday humdrum life to another as humdrum or perhaps more so. And how long would our happiness last? What would happen to her in case I was ill, in case I died, or if we simply grew cold to one another?

    “And she apparently reasoned in the same way. She thought of her husband, her children, and of her mother, who loved the husband like a son. If she abandoned herself to her feelings she would have to lie, or else to tell the truth, and in her position either would have been equally terrible and inconvenient. And she was tormented by the question whether her love would bring me happiness — would she not complicate my life, which, as it was, was hard enough and full of all sorts of trouble? She fancied she was not young enough for me, that she was not industrious nor energetic enough to begin a new life, and she often talked to her husband of the importance of my marrying a girl of intelligence and merit who would be a capable housewife and a help to me — and she would immediately add that it would be difficult to find such a girl in the whole town.

    “Meanwhile the years were passing. Anna Alexyevna already had two children. When I arrived at the Luganovitchs’ the servants smiled cordially, the children shouted that Uncle Pavel Konstantinovitch had come, and hung on my neck; every one was overjoyed. They did not understand what was passing in my soul, and thought that I, too, was happy. Every one looked on me as a noble being. And grown-ups and children alike felt that a noble being was walking about their rooms, and that gave a peculiar charm to their manner towards me, as though in my presence their life, too, was purer and more beautiful. Anna Alexyevna and I used to go to the theatre together, always walking there; we used to sit side by side in the stalls, our shoulders touching. I would take the opera-glass from her hands without a word, and feel at that minute that she was near me, that she was mine, that we could not live without each other; but by some strange misunderstanding, when we came out of the theatre we always said good-bye and parted as though we were strangers. Goodness knows what people were saying about us in the town already, but there was not a word of truth in it all!

    “In the latter years Anna Alexyevna took to going away for frequent visits to her mother or to her sister; she began to suffer from low spirits, she began to recognize that her life was spoilt and unsatisfied, and at times she did not care to see her husband nor her children. She was already being treated for neurasthenia.

    “We were silent and still silent, and in the presence of outsiders she displayed a strange irritation in regard to me; whatever I talked about, she disagreed with me, and if I had an argument she sided with my opponent. If I dropped anything, she would say coldly:

    ” ‘I congratulate you.’

    “If I forgot to take the opera-glass when we were going to the theatre, she would say afterwards:

    ” ‘I knew you would forget it.’

    “Luckily or unluckily, there is nothing in our lives that does not end sooner or later. The time of parting came, as Luganovitch was appointed president in one of the western provinces. They had to sell their furniture, their horses, their summer villa. When they drove out to the villa, and afterwards looked back as they were going away, to look for the last time at the garden, at the green roof, every one was sad, and I realized that I had to say goodbye not only to the villa. It was arranged that at the end of August we should see Anna Alexyevna off to the Crimea, where the doctors were sending her, and that a little later Luganovitch and the children would set off for the western province.

    “We were a great crowd to see Anna Alexyevna off. When she had said good-bye to her husband and her children and there was only a minute left before the third bell, I ran into her compartment to put a basket, which she had almost forgotten, on the rack, and I had to say good-bye. When our eyes met in the compartment our spiritual fortitude deserted us both; I took her in my arms, she pressed her face to my breast, and tears flowed from her eyes. Kissing her face, her shoulders, her hands wet with tears — oh, how unhappy we were! — I confessed my love for her, and with a burning pain in my heart I realized how unnecessary, how petty, and how deceptive all that had hindered us from loving was. I understood that when you love you must either, in your reasonings about that love, start from what is highest, from what is more important than happiness or unhappiness, sin or virtue in their accepted meaning, or you must not reason at all.

    “I kissed her for the last time, pressed her hand, and parted for ever. The train had already started. I went into the next compartment — it was empty — and until I reached the next station I sat there crying. Then I walked home to Sofino. . . .”

    While Alehin was telling his story, the rain left off and the sun came out. Burkin and Ivan Ivanovitch went out on the balcony, from which there was a beautiful view over the garden and the mill-pond, which was shining now in the sunshine like a mirror. They admired it, and at the same time they were sorry that this man with the kind, clever eyes, who had told them this story with such genuine feeling, should be rushing round and round this huge estate like a squirrel on a wheel instead of devoting himself to science or something else which would have made his life more pleasant; and they thought what a sorrowful face Anna Alexyevna must have had when he said good-bye to her in the railway-carriage and kissed her face and shoulders. Both of them had met her in the town, and Burkin knew her and thought her beautiful.

    About Love


  • Motivational and Inspiring Short Stories About Life

    Motivational and Inspiring Short Stories About Life

    Motivational and Inspiring 5 Short Stories About Life; When life has got you in a slump, turn to these inspirational short stories. Not only is reading them like getting an internet hug for the soul, but they just may spark an idea or a change in you for the better. Read on and get ready how to keep a smile yourself.

    Here is the article to explain, 5 best Short Story for Life – Motivational and Inspiring.

    The following few Motivational and Inspiring Short Stories below are;

    1. Everyone Has a Story in Life

    A 24-year-old boy seeing out from the train’s window shouted…!

    “Dad, look the trees are going behind!”
    Dad smiled and a young couple sitting nearby; looked at the 24-year old’s childish behavior with pity, suddenly he again exclaimed…

    “Dad, look the clouds are running with us!”

    The couple couldn’t resist and said to the old man…!

    “Why don’t you take your son to a good doctor?” The old man smiled and said…“I did and we are just coming from the hospital, my son was blind from birth, he just got his eyes today.”

    Every single person on the planet has a story. Don’t judge people before you truly know them. The truth might surprise you.

    2. Shake off Your Problems

    A man’s favorite donkey falls into a deep precipice. He can’t pull it out no matter how hard he tries. He, therefore, decides to bury it alive.

    The soil pore onto the donkey from above. The donkey feels the load, shakes it off, and steps on it. More soil pours.

    It shakes it off and steps up. The more the load was poured, the higher it rose. By noon, the donkey was grazing in green pastures.

    After much shaking off (of problems) And stepping up (learning from them), One will graze in GREEN PASTURES.

    3. The Elephant Rope

    As a man was passing the elephants, he suddenly stopped, confused by the fact that these huge creatures were being held by only a small rope tied to their front leg. No chains, no cages. It was obvious that the elephants could, at any time, break away from their bonds but for some reason, they did not.

    He saw a trainer nearby and asked why these animals just stood there and made no attempt to getaway. “Well,” the trainer said, “when they are very young and much smaller we use the same size rope to tie them, and, at that age, it’s enough to hold them. As they grow up, they condition to believe they cannot break away. They believe the rope can still hold them, so they never try to break free.”

    The man was amazed. These animals could at any time break free from their bonds but because they believed they couldn’t, they were stuck right where they were.

    Like the elephants, how many of us go through life hanging onto a belief that we cannot do something, simply because we failed at it once before?

    Failure is part of learning; we should never give up the struggle in life. This is the best Inspiring Short Stories.

    4. Potatoes, Eggs, and Coffee Beans

    Once upon a time a daughter complained to her father that her life was miserable and that she didn’t know how she was going to make it. She was tired of fighting and struggling all the time. It seemed just as one problem was solved, another one soon followed.

    Her father, a chef, took her to the kitchen. He filled three pots with water and placed each on a high fire. Once the three pots began to boil, he placed potatoes in one pot, eggs in the second pot, and ground coffee beans in the third pot.

    He then let them sit and boil, without saying a word to his daughter. The daughter moaned and impatiently waited, wondering what he was doing.

    After twenty minutes he turned off the burners. He took the potatoes out of the pot and placed them in a bowl, He pulled the eggs out and placed them in a bowl.

    He then ladled the coffee out and placed it in a cup. Turning to her he asked. “Daughter, what do you see?”

    “Potatoes, eggs, and coffee,” she hastily replied.

    “Look closer,” he said, “and touch the potatoes.” She did and noted that they were soft. He then asked her to take an egg and break it. After pulling off the shell, she observed the hard-boiled egg. Finally, he asked her to sip the coffee. Its rich aroma brought a smile to her face.

    “Father, what does this mean?” she asked.

    continue…

    He then explained that the potatoes, the eggs and coffee beans had each faced the same adversity– the boiling water.

    However, each one reacted differently.

    The potato went in strong, hard, and unrelenting, but in boiling water, it became soft and weak.

    The egg was fragile, with the thin outer shell protecting its liquid interior until it was put in the boiling water. Then the inside of the egg became hard.

    However, the ground coffee beans were unique. After they were exposed to the boiling water, they changed the water and created something new.

    “Which are you,” he asked his daughter. “When adversity knocks on your door, how do you respond? Are you a potato, an egg, or a coffee bean? “

    Moral: In life, things happen around us, things happen to us, but the only thing that truly matters is what happens within us.

    Which one are you?

    5. A Dish of Ice Cream

    In the days when an ice cream sundae cost much less, a 10-year-old boy entered a hotel coffee shop and sat at a table. A waitress put a glass of water in front of him.

    “How much is an ice cream sundae?”

    “50 cents,” replied the waitress.

    The little boy pulled his hand out of his pocket and studied a number of coins in it.

    “How much is a dish of plain ice cream?” he inquired. Some people were now waiting for a table and the waitress was a bit impatient.

    “35 cents,” she said brusquely.

    The little boy again counted the coins. “I’ll have the plain ice cream,” he said.

    The waitress brought the ice cream, put the bill on the table and walked away. The boy finished the ice cream, paid the cashier and departed.

    When the waitress came back, she began wiping down the table and then swallowed hard at what she saw.

    There, placed neatly beside the empty dish, were 15 cents – her tip.

    Motivational and Inspiring Short Stories About Life
    5 Motivational and Inspiring Short Stories About Life.
  • How to Preparation of CAT Exams in 4 or 5 months?

    How to Preparation of CAT Exams in 4 or 5 months?

    How to Preparation of CAT Exams in 4 or 5 months?


    Going by the previous year’s schedule, CAT will be conducted in the first week of December. That leaves roughly 4 or 5 months/150 days for preparation. CAT is the one stop solution for all such students who dream of getting an MBA degree from one of the best management institutes in India. To top it, CAT score is not just accepted by IIMs but by many other good B-schools. Though CAT is not deemed as a tough exam but is tricky to clear.

    Students who have cleared the exam in the past, claim that the exam is not tough but requires careful and strategic planning in order to clear it. Here we will discuss what should be the preparation strategy for students who will begin preparing for CAT exam now.

    Preparation of CAT Exams in 4 or 5 months


    How to Preparation of CAT Exams in 4 or 5 months?

    According to many experts and students who have cleared CAT earlier, this is the right time to prepare for CAT exam.

    The first 2-3 months should be devoted to learning the basic concepts and brushing up the fundamentals of the topics. During this time, it would be a good practice to pick up mock tests and previous year question papers and begin solving them. In the beginning, the frequency of solving mock tests should be one to two in a week. This way, not only will you be able to analyze where you are in terms of your knowledge, you will also get to measure your progress as you go along with your preparation.

    Contrary to popular opinion you do not need to study for 8-12 hours every day. Even 4-hour study duration is enough, given that you are focused and attentive toward what you study.

    You will also need to categorize the topics to be covered as most difficult, difficult, moderate and easy. This will help you in a directed preparation and hone your strong topics and work harder on the weak ones.

    Learn more than one method to solve a question. During the exam, knowing more than one way of solving a question will help you in solving questions more accurately. Accuracy is one of the key factors in scoring a high percentile in CAT exam.

    While preparation makes sure that you pay equal attention to all the three sections. Sometimes students who are good in English, pay less attention to preparing for VRC section and end up scoring badly despite having a strong grasp on the language.

    Make a routine and schedule for studying and stick to it. Incorporating CAT preparation in and as your daily schedule will help you stick to your goal and will deliver desired end result.

    Toward the last phase of your preparation, do not start learning new topics. The last phase especially the weeks leading up to the exam day should be devoted to solving mock tests entirely. During this time you should be solving at least two mocks in a day.

    Many Cat toppers swear by mock test solving and have said that solving mock tests helped them get in the right mind frame and solving CAT questions while sticking to the rules of the exam became second nature to them.

    How to Preparation of CAT Exams in 4 or 5 months?


  • Requirement for CAT Application Eligibility

    Requirement for CAT Application Eligibility

    The requirement for CAT Application Eligibility


    CAT will be conducted by IIM Lucknow. While there is still time left before the official notification is out and the real race begins, why not go through the eligibility requirements essential for appearing in the exam. In general terms, anyone with a graduate degree can appear for the CAT exam. However, there are certain other conditions which must be fulfilled or else a candidate will be disqualified from appearing in the exam. There is also an important question of work experience and if it is an essential requirement for CAT or not.

    While understanding the eligibility requirement is fairly easy, sometimes students are at loggerheads with what is considered as a degree equivalent to a graduate degree. Also, students are often under the impression, that it is compulsory to have some work experience before they appear for CAT exam. In this article, we will explain both academic eligibility and the question of work experience.

    CAT Eligibility Criteria


    • A candidate applying for CAT exam must have a Bachelor’s degree in any discipline with 50% marks or equivalent CGPA.
    • The minimum percentage required for candidates belonging to Scheduled Caste (SC), Scheduled Tribe (ST), and Persons with Disability (PWD) category is 45% or equivalent CGPA.
    • The degree must have bone obtained from a university incorporated by an Act of Parliament or State Legislature in India or institution recognized by UGC or must possess an equivalent recognition from MHRD, Government of India.
    • Candidate’s appearing in the final year of their qualifying examination can also appear for the CAT exam on the condition that they produce a certificate issued by the Principal/Registrar of their university/institute stating that they have completed all the degree requirements at the time of their admission.
    • Candidates who have completed CA/CS/ICWA can also apply. The percentage requirement for these candidates will be same as mentioned in the points above.
    • The candidate must hold a Bachelor’s Degree, with at least 50% marks or equivalent CGPA (45% in case of the candidates belonging to Scheduled Caste (SC), Scheduled Tribe (ST) and Persons with Disability (PWD)/Differently Able (DA) category) awarded by any of the Universities incorporated by an act of the central or state legislature in India or other educational institutions established by an act of Parliament or declared to be deemed as a University under Section 3 of the UGC Act, 1956, or possess an equivalent qualification recognized by the Ministry of HRD, Government of India.
    • The percentage of marks obtained by the candidate in the bachelor’s degree would be calculated based on the practice followed by the university/institution from where the candidate has obtained the degree. In case the candidates are awarded grades/CGPA instead of marks, the conversion of grades/CGPA to percentage of marks would be based on the procedure certified by the university/ institution from where they have obtained the bachelor’s degree. In case the university/ institution does not have any scheme for converting CGPA into equivalent marks, the equivalence would be established by dividing the candidate’s CGPA by the maximum possible CGPA and multiplying the result with 100.
    • Candidates appearing for the final year of bachelor’s degree/equivalent qualification examination and those who have completed degree requirements and are awaiting results can also apply. If selected, such candidates will be allowed to join the programme provisionally, only if she/he submits a certificate latest by before July or August from the Principal/Registrar of her/his College/Institute (issued on) stating that the candidate has completed all the requirements for obtaining the bachelor’s degree/equivalent qualification on the date of the issue of the certificate.
    • IIMs may verify eligibility at various stages of the selection process, the details of which are provided at the website www.iimcat.ac.in. Applicants should note that the mere fulfillment of minimum eligibility criteria will not ensure consideration for shortlisting by IIMs. Prospective candidates must maintain a valid and unique email account and a phone number throughout the selection process.

    List of Equivalent Qualifications


    1. Bachelor’s degree in Engineering/Technology (4 years after 10+2/Post B.Sc./Post Diploma ) or B.E/B.Tech equivalent examinations, of Professional Societies, recognized by MHRD/UPSC/AICTE (e.g. AMIE by Institution of Engineers -India, AMICE by the Institute of Civil Engineers-India).

    2. Any Qualification recognized by Association of Indian Universities New Delhi, which is equivalent to a Bachelor’s Degree awarded by UGC recognized University/Institutions.

    3. Cases not covered above equivalency certificate to be produced by Association of Indian Universities New Delhi.

    Reservations


    • As per the Government of India requirements, 15% of the seats are reserved for Scheduled Caste (SC) and 7.5% for Scheduled Tribe (ST) candidates. 27% of seats are reserved for Other Backward Classes candidates belonging to the “non- creamy” layer (NC – OBC).
    • For an updated central list of state – wise OBCs eligible for availing the benefit of reservation and information in respect of the creamy layer, visit the website http://www.ncbc.nic.in.
    • In the case of NC – OBC category, the castes included in Central List (available at http://www.ncbc.nic.in) of NC – OBC by the National Commission of Backward Classes, Government of India as on last day of registration will be used. Any subsequent changes will not be effective for CAT.
    • As per the provision under section 39 of the PWD Act, 1995, 3% seats are reserved for Differently Abled (DA) candidates. The three categories of disability are – 1) low vision blindness, 2) hearing impairment and 3) Locomotor disability/Cerebral Palsy. This provision is applicable if the candidate suffers from any of the listed disabilities to the extent of not less than 40%, as certified by a medical authority as prescribed and explained in the said Act.
    • The candidates belonging to categories for which seats are reserved need to note and read the eligibility requirements carefully before applying. It should be noted that while it is the endeavor of IIMs that the candidates belonging to SC/ST/PWD/Non – Creamy OBC categories join the Programme in proportions mandated by the law, they have to meet the minimum eligibility criteria and a certain minimum level of performance in the admission process.
    • The candidates should read carefully the description of admission process followed by each IIM on their respective websites. No change in the category will be entertained after the closure of registration window. Hence, applicants are advised to give attention while registering.

    Note for SC/ST, NC- OBC, and DA Candidates


    • If you belong to SC or ST categories, your caste/tribe must be listed in the Government of India schedule. The caste certificate that you send to IIM should be in the Government approved format and should clearly state: (a) Name of your caste/tribe; (b) Whether you belong to Scheduled Caste or Scheduled Tribe; (c) District and the State or Union Territory of your ordinary residence; and (d) the appropriate Government of India schedule under which your caste/tribe is approved by it as Scheduled Caste or Scheduled Tribe.
    • A copy of the SC/ST and /or PWD (DA) certificate(s) must be uploaded at the time of CAT Application online. Failure to upload a copy of the caste/class certificate will result in the rejection of your CAT registration.
    • The SC/ST and/or PWD (DA) certificate(s) must be shown and a photocopy should be submitted at the time of interviews. Moreover, the certificate(s) must be submitted at the time of joining programs of any of the IIMs.
    • If you belong to the Non – Creamy Other Backward Classes (NC – OBC), you must produce the NC – OBC certificate duly signed by the competent authority and enclose its photocopy at the time of interviews. Moreover, the certificate must be submitted at the time of joining programs of any of the IIMs. Failure to do so during the post CAT selection process will result in you not being considered under the reserved category.

    Work Experience Requirement


    Having a prior work experience is not a compulsory requirement for candidates appearing in CAT. The application form does ask for work experience details but it is not mandatory.

    However, during the final selection of candidates, work experience is given some weight-age by the IIMs. The exact weight-age given to work experience is never revealed by the IIMs but it varies from IIM to IIM.

    The bottom line is that work experience does not come into play till the last stage of final selection and even then it does not play a deciding factor. IIMs have been known to have a mixed batch comprising of both fresh graduates and students with work experience.

    Requirement for CAT Application Eligibility