Analytics for Smart Decisions The Wonderful World of Big Data, Business Analytics and Business Intelligence - Demystified

What is Analytics and Data Science? Using statistical, mathematical and computer science tools to analyze, explain and predict information Statistics - Study of the collection, organization, analysis, interpretation and presentation of data Theoretical statistics – the mathematical basis of the process of statistical analysis. Most research and work on finding new tools, fixing errors in existing tools and improving them Applied Statistics – using the existing tools of statistics on certain data to improve our understanding of the problem in hand But analytics is not just statistics It uses tools from computer science to analyze large quantities of data to generate meaningful trends and patters Especially useful for studying human choice behavior

This course is about Decision Science… and not just Data Science The idea behind the course is to use analytical tools to help take decisions The focus is not on data, but on decisions Decision science is a complex field which involves Psychology – or how people take decisions Decision Theory – using decision trees and mathematical tools to take calculate expected values of multiple projects Game Theory – How interpersonal or intercorporate competition affects outcomes (or your profits) Data Sciences – How data can be used to make better decisions

Decision Science is an art-science-tech blend Professionals who have the right mix of knowledge in the three pillars of Analytics – the Technology, the Science and the Art will succeed The technology includes simple software program like Excel to advanced ones like Python and PERL, simple database management systems like Access to more advanced SQL or MapReduce and to pure coding skills in statistical software like SAS or R Statistics is the key science behind analytics. Simple statistical and econometric tools like correlation and regression to much newer developments and complex multivariate methods are all used to model and make sense of the large data sets However, it is the soft skills, the art of management and a keen understanding of human behavior, which is essential in taking decisions based on this science and technology.

Remember GIGO – Garbage In Garbage Out Your model or analytics supported decision is only as good as your 1.Data; 2.Your analysis of the data; and 3.The understanding of that analysis Garbage in any of these three will lead to garbage decisions

So what exactly are we trying to get at? For customer data – we want to find out the underlying “data generating process” Look inside your HEAD! Habits! Let’s discuss

Where can data work? Marketing – By clustering your customers into different buckets and creating targeted ads and coupons for them Retail – How do we design our shop? Beer next to what? Bread and what together? Operations – Your bike routes can be optimized using GPS data, time series analysis and data analytics Risk – Especially useful for Banking, Financial Service and Insurance, but also important for Treasury departments within corporations In Insurance, try to calculate the likelihood of someone falling sick HR Analytics – Can help you take very important decisions, like – should we train a HiPo or not – because if we train, s/he might leave, if we do not, they will not improve Or, using simple models to tell us the probability of how many customers can show up in our shop at the same time What is the likelihood that 2 people out of 5 will not show up to work tomorrow?

Pizzalytics! IBM Papa Gino’s Papa Gino’s CIO Much more of restaurant analytics – from Pricing to Coupons SLYZikiEIB2 SLYZikiEIB2

Domino’s customer-analytics-help-boost-sales customer-analytics-help-boost-sales

Reading for Tomorrow Analytics 3.0 – by Tom Davenport Making Advanced Analytics work for You These will not be a part of the test