Discovering, Not Finding. Practical Data Mining for Practitioners: Level II. Advanced Data Mining for Researchers : Level III

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1 Predicitve DATA EMPOWERING DECISIONS Data Mining & Predicitve Training (DMPA) is a set of multi-level intensive courses and workshops developed by Cognitro team. it is designed to enable analysts, researchers and professionals to undertsand, master and apply the concept, tools and technology of data mining and predictive analytics so that they can maximally utilize it at thier home institution. Analyze Data, Discover Information, Gain Knowledge, Attain Wisdome. Typical Data Mining Tasks Rate customers by their propensity to respond to a marketing campaign or sales offer Identify cross-sell marketing opportunities Forecast future stock value based on historical data Detect fraud and abuse in insurance and finance Predict the risk of declining revenues and profits Isolate root causes of an outcome in clinical studies Predict potential defaulters on loan or credit card Discovering, Not Finding In today s business environment, almost every organization in every type of industry stands to face the same technical challenge, and your company is one that is most likely to be trapped in the same vicious cycle. Routinely, new data are sampled, collected, stored, analyzed, interpreted and then possibly archived for another round of analysis and hopefully better interpretation. The goal is ultimately to extract from the data an important piece of information that is vital for the decision making process. But as the volume of your data increases, uncovering these information becomes very much like finding the proverbial needle in the haystack. In this case, the needle is that single piece of intelligence your business needs and the haystack is the large data warehouse you've built up over a long period of time. Traditional statistics can be useful in summarizing the past. But to be truley Predictive! to be able to know beofrehand how your customers will respond in the future, detect fraudulent online transactions, or score your loan applicants based on an array of attributes, there is only one place to turn Data Mining and Predictive. By learning from your abundant historical data, data mining provides something beyond standard business reports and sales forecasts: the ability to fast-forward into the future and discover critical insights your competition doesn t have its hands on. Cognitro Data Mining and Predictive Data Mining for Biginners : Level I Practical Data Mining for Practitioners: Level II Advanced Data Mining for Researchers : Level III 1 Cognitro

2 Course Level-I : Data Mining for Beginners - Business and Data Analysts - Marketing personals, IT managers and operational directors - QA officers, managers and auditors. - Functional Managers - Decision makers and investors of any kind involved with analyticss Data Mining for Beginners This course offers a comprehensive look into the world of data mining and provides methodological and practical coverage of state-of-art data mining techniques to identify expected and unexpected trends in data. It highlights their underlying concept and as well as their applicability to accumulated data repositories throughout the entire project lifecycle from business analysis and data understanding to modeling and deployment. Moreover, you will be able to apply what you have learned within a state-of-art data mining workbench using real-life data. Attendants will be exposed to the most popular tools of data mining and predictive analysis, application examples, live illustrations and resources. An intensive overview of techniques, best practices and case studies. -Develop a solid understanding of the science of data mining and its terminology -Learn the most-commonly used data mining models and thier classifications. -Develop modeling skills to allow you to apply the right Data Mining Model to the appropriate business problem. -Learn how to test and evaluate a Data Mining model and interpret the results -Understand the data mining practices and how to apply at your home institution DATA MINING TECHNIQUES - Introduction to Data Mining - Definition of data mining - What distinguishes data mining from statistical analysis, Query/Reporting, and OLAP - Descriptive Models and Predictive Models - Divisions of data mining algorithms - Supervised and Unsupervised learning (and example business uses) Categorical target, vs. Continuous target - Cluster analysis - Anomaly detection - Practical Issues in Data Mining - Introduction to CRISP DM - Preparing data, building data mining - Testing and validation - Transporting a data mining model (PMML) across platforms - Business areas where data-mining/predictivemodeling can make contributions - Case Studies 1) Cross sell / Up-sell / Balance growth 2) Traditional direct marketing (mail & phone) 3) Targeted recommendations at every custom 2 Bayesian Model Logistic Regression Decision Tree Algorithm Neural Network Verizon Wireless was able to reduce its churn from over 2 per cent to below 1.5 per cent using the data mining tools. It was also able to expand marketing campaign from 40-60,000 mailers per month to a 400,000 mails per month No prior knowledge is required Cognitro

3 Course Level-II : Practical Data Mining For Practitioners - Data Mining practitioners - Department heads and managers of marketing and business intelligence - Database analysts and consultants - Anyone who are involved in managing data mining projects Practical Data Mining This course digs deep into the world of data mining and business intelligence (BI) and presents a detailed view of all aspects of managing a data mining project, beginning with assessment of business goals and requirements, identifying the right data, and ending with model deployment and evaluation. It sheds light on common pitfalls and mistakes made by data mining practitioners and exposes elements of success that yields the highest return on project investment. A tactical drill-down of the data mining process, methods, techniques and resources. - Plan and manage your data mining projects effectively using the industry practice of CRISP-DM framework. Learn what makes or breaks your analytics project - Learn how to to substantially reduce your project preparation time, costs and risks, and interpret the results. - Learn how to transform your organization into a truley Predictive enterprise. - Data Minining Project Management - CRISP DM - Industry Standards - Business understanding - Data understanding - Data preparation - Model Building - Model testing and evaluation - Model Deployment - Top ten Common mistakes known to cause project failure - Case Study - Data Mining Vs. Business Intelligence (BI) - How does data mining and predictive analytics supports BI platforms - Overview of data mining model development tools (SPSS, SAS, R, ODM, MatLab, etc...) - How to transport models across analytical and BI platforms - How to assess your data mining project - Top ten indicators your institution is a Predictive enterprise - Case Study Basic knowledge of data mining 3 Citibank was able to increase marketing response rate by 30% on direct mail after implementing basket market analysis to cross-sell the right products to the right customers Cognitro

4 Course Level-III : Advanced Data Mining for Reseaechers - Data Mining Practitioners and analytics models builders -Quantitiative Experts and Analysts - Decision Support System Developers. - Anyone who would like to be at the forefront of This course picks up where the fundamentals in our basic course left off. It s the perfect complement for those wanting to take full advantage of state-of-the-art practices in data mining and modeling. It offers data mining practitioners a deep dive into sophisticated analytical models, with the opportunity to dissect their predictive algorithms. It exposes the underlying conceptual design and the model parameters that differentiate one from the other. Practical considerations are given to accuracy and performance as they pertain to the business case, applied datasets, and the IT environment where these analytics are deployed. A hands-on application workshop as an extension to Data Mining: Level II. Advanced Data Mining - How advanced methodologies can reveal, understand, and capitalize on hidden data patterns - How to match multiple leading-edge algorithms for varying types of problem solving - How to uncover important associations across varying groups of items - How to evaluate the accuracy and performance of your data mining model. - Methods And Applications -Predictive vs. Descriptive -Supervised vs. Unsupervised - Solving Dimensional Problems -Principal Component -Artificial Neural Networks - Association Analysis - Market Basket Analysis -Sequential Pattern Mining - Supervised Methods : -CHAID - CART - Supervised Methods (Cont.): -Discriminant Analysis -Multinomial Logistic Regression - Unsupervised Methods : - Hierarchical Cluster Analysis - K-Means Cluster Analysis - Self Organizing Maps - Web Data and Text Mining - How to choose the right metrics to judge the success of your analytical model - What can you do to improve the outcomes of your data mim Basic knowledge of data mining 4 WalMart Store was able to increase its revenues by 20% after deploying a predictive model that enabled the store to optimize the way in which it shelves its items. Cognitro

5 DATA EMPOWERING DECISIONS About Cognitro Courses Cognitro Training program is designed to explain the art and science of analytics in simple and easy language. The main goal is to enable average business analysts and professionals to understand analytics terminology, capabilities, limitations, risks, rewards, and best practices to reap its full benefits and obtain the maximum return on investment. All courses contain a balance mixture of theory and practice with interactive breakout sessions. The courses provide methodological and practical coverage of Data Mining and Predictice, offering a comprehensive look into best practices and underlying its value to corporate performance and profitability. About Cognitro Speakers Our seasoned instructors are PhD researchers and developers of data mining and predictive analytics algorithms with years of deep involvement in innovative research and development of real-world data mining solutions.the speakers, which include scientists, professionals, and analysts from Cognitro, have been working in the trenches and leading data mining engagements at top US banks. They make the course material real using examples and case studies from these banks. Attendants will be exposed to the most popular data mining techniques and software tools and will engage in a hands-on demonstration. Attendants also recieve a certificate of attendance at the end of each course. Contact Us... About Cognitro Cognitro is a US-based company specialized in providing advanced business analytics solutions and data mining services. We help clients, reduce risk, optimize marketing, uncover fraud and retain customers, by maximizing the value of data to make more insightful and informed business decisions. For further information, please contact your Cognitro representative or call/ Phone: Web: Cognitro

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