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Harnessing the Power of Analytics
Ingest Infer Interpret
YOGESH DANDAWATE
Big Data AnalyticsBig data analytics is the process of examining large amounts of data of a variety of types (big data) to uncover hidden patterns, unknown correlations and other useful information. Such Information can provide advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue.
Descriptive Analytics
• Answers the question, "What happened in the business?
• It looks at data and information to describe the current business situation in a way that trends, patterns and exceptions become apparent.
Diagnostic Or Inquisitive Analytics
• Answers the question, "Why is something happening in the business?"
• It is study of data to validate / reject business hypotheses. This includes analytical drill downs into data, statistical analysis, factor analysis, etc.
Predictive Analytics
• Answers the question, "What is likely to happen in the future?"
• Here data modeling and forecasting are used to determine future possibilities
• Predictive analytics uses data to determine the probable future outcome of an event or a likelihood of a situation occurring.
Prescriptive Analytics
• Answers what, when, why questions
• For example, what should a business do to retain key customers? How can businesses improve their supply chain to enhance service levels while reducing costs?
Created using http://www.mu-sigma.com/analytics/ecosystem/dipp.html
What are Big Data Dimensions?
Volume• Data at Rest• Terrabytes to
Exabytes of existing data to process
Velocity• Data in Motion• Streaming data,
near real time response needs
Variety• Data in multiple
forms• Structured,
unstructured, text, multimedia data
Veracity• Data in doubt• Uncertain
information (incomplete, inconsistent, ambiguous, approximate data)
Analytics in Retail and FMCGApplication Areas
• Identifying of Potential customers• Understanding customer churn• Understanding customer sentiment• Improving/Personalizing Customer
Experience• Recommending products to
Customers• Understand customer behavior• In-store shopper movement
analysis• Loyalty Program Management
• Content Analytics• Demand Forecasting• Operations Analytics• Enterprise Information Management• Supply Chain Optimization• Scheduling Preventive Maintenance
and Repairs
Technology Elements• Content Analytics
• Speech/Audio Analytics• Video Analytics• Text Analytics• Web Analytics
• Sentiment Analysis• Recommendation Engines• Gesture Analytics
• Eyeball Tracking• Expression Analysis
• Social Media Analytics• Activity Stream/Click Analytics• Storage and Search Technologies• Active News and Event Analytics
• Stock & Re-Arrange Essentials on shelves
• Reroute Shipments
• Notify/Update/Recommend Customers
• Enhance store security
Weather Forecast Real Time Decision MakingDisaster management
Call Center Management• What are common customer
complaints?
• Locations from where maximum complaints are getting registered?
• Are issues attributed to Operational Efficiency, Equipment efficiency, People Efficiency ?
• What is the general sentiment of the product/s ?
• Which is the most popular product ?
• Customer feature recommendations?
• Average time for query resolution?
• Query/ Feedback /Complaints Categorization
• Similar queries and their resolutionsStatistics
Geo tagging
Feedback
Complaints Speech Analytics
Text Analytics
Kinect
Expression Analyzer
Confused
Needs Assistance
Enhancing In Store Experience