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Big data analytics bhawani nandan prasad
The document discusses big data, business analytics, and machine learning techniques. It covers topics like supervised learning, unsupervised learning, decision trees, neural networks, and analytics software tools including Hadoop, Cassandra, and SAS. It also discusses domains like retail analytics, financial analytics, and building an enterprise analytics strategy.
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Big data analytics bhawani nandan prasad
- 1. Big Data Business Analytics -BhawaniNandan Prasad B.E. Computer Science MBA Marketing and Strategy
- 2. Analytics Model andMethodology Understanding Machine learning techniques • Supervised Learning • Unsupervised Learning • Semi-Supervised Learning Machine learning paradigms • Decision Trees • Support Vector Machines • Neural Networks • Ensemble Methods • Bayesian Approaches • Logistic Regression, Linear Regression, Mulitvariate • Random Forests • Matrix Factorization • Ontology Mapping Pattern Recognition • Image processing • Statistical patterns • Natural Language Processing – Text Mining, Searching Statistics • Variance and Standard Deviation • Probability, Probability distribution ( Uniform Bernoulli Binomial Poisson Negative Binomial Lognormal Exponential Gamma Chi-Square t & F distribution, SVM, K-means, KNN) • The Central Limit Theorem • Sampling and statistical inference • Hypothesis testing • Correlation, Covariance, Forecasting, Classification, Clustering • Heteroskedasticity • Generalized linear Model • ARIMA and Time Series Model • UPSELL Model algorithm • Linear predictor and Link Function • Score Card Performance-Rank, KS stat • CHAID (Chi-Square Automatic Interaction Detector) • C&ART (Classification and Regression Tree) • QUEST (Quick Unbiased Efficient Statistical Test)
- 3. Analytics Software Tools BIGData Tools • Apache Hadoop Stack Hadoop, Pig, Hive, Lucene, NLP, Aster data, MapReduce, HDFS, HBase, Oozie, Avro, Zookeeper, Sqoop, Impala and Flume • Platform HP Vertica, HP Haven NOSQL Tools • Cassandra, MangoDB, CouchDB, Marklogic, Key-Value, RDF tripple Stores, Neo4j Graphs , XMLDB Semantic Web Search Ontology tools • IBM Minerva, Jena, Neon, Neo4j, Protégé, Neologism, Knoodl, Enterprise Architect Analytics Tools • SAS, SAS EGMiner, SAS Statistics, SPSS, Knime, R, Mahout, Microsoft APS Advanced Analytics & Visualization • SAS, IBM SPSS, IBM Watson analytics, Tableau, Spotfire, Google Analytics, Microsoft HDInsight, Pentaho Analytics Semantic Web Search • URI, RDF, RDF schema, SPARQL, Triple stores, Linked-Data, Textonomy, Web Ontology Languages like OWL Lite / DL / Full, SPARQL • Web Application Server : Tomcat 6.0, JBoss 4.2, Weblogic, Wesphere and Web Logic 8.1 • Application Framework: Struts 1.3, spring 2.5, Hibernate 3.3, Jasper Reports, Ajax, JUnit and JAXB • Java Technologies – Core Java, J2EE, JSP, EJB, Digital commerce, Electronic Commerce, UML, Google toolkit
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- 6. Analytics Category Domain •Diagnostic Analytics Gain insight Why did it Happen • Descriptive Analytics ( What is happening ) Gain insight from historical data with reporting, scorecards, clustering etc • Predictive / Discovery Analytics ( What is likely to happen ) Predictive modeling using statistical and machine learning techniques • Prescriptive Analytics ( What should I do about it ) Recommend decisions using optimization, simulation etc • Decision Science Analytics Recommend decisions using Machine Learning, Decision Science Algorithms etc
- 7. Types of AnalyticsSolutions
- 8. Analytics Function DomainUnderstanding •Behavioral Analytics •Collections Analytics •Customer Analytics •Digital Marketing Analytics •Financial Capital Market Analytics •Financial Risk and Regulatory Analytics •Fraud Analytics •Health Care Analytics •Interactive Media Command Center Analytics •IT Operations Analytics •Marketing and Sales Operations Analytics •Pricing Analytics •Product Quality / Performance Analytics •Retail Analytics •Risk & Credit Analytics •Situational Awareness Analytics Foresight •Supply Chain Analytics •Telecommunications Analytics •Warranty Analytics – Early Defect Detection •Workforce Analytics
- 9. Retail Analytics Understanding CustomerAnalytics • Customer Acquisition • Customer Loyalty & Retention • Web Analytics • Behavioral Segmentations • Customer Demographic • Customer Psychographics Market Analytics • Market Basket Analysis / recommendation Engine • Marketing Mix • Bad Health and Reputation • Multi-Chanel Campaign Effectiveness and optimization • Cross Channel Marketing • Campaign Management Merchandizing & Planning • Store Localization & Cluster Analysis • Product Pricing & Elasticity Analysis / Markdown optimization • Assortment & shelf space optimization • Out of Stock Analysis & Management Demand Creation & Supply Chain • Inventory Planning & Replenishment Analysis • Demand Forecasting ( Halo & Cannibalization Effects ) • Product Flow Optimization
- 10. Financial Stock MarketAnalytics Understanding • What if Analysis • Charting Corner • Derivative Strategy Builder • Market Information • Mutual Fund Comparison • Portfolio Doctor • Power Screener • Stock Screener • Stock Comparison • Strategies • Watch list • Xtreme Trader
- 11. Building Enterprise AnalyticsStrategy Holistic Approach: Match Data Types, Tools, Skills, & Delivery