Business Analytics Primer
Business analytics is part of the SMAC set of technologies that is impacting Enterprises both Digital as well as Traditional Enterprises. As IT professionals we can comprehend the impact of Mobility, Social as well as Cloud on Enterprises as we deal with them and know how it impacts enterprises positively. However when we talk about Analytics it is like one big elephant and like blind men we are trying to figure out what Analytics is all about and Why is it becoming Critical for enterprises. The objective of the post to share some of my thoughts around Analytics.
The challenge of Enterprises is to take react and take decisions in response to environmental changes. Enterprises need all the help they can get them to make informed decisions.
The below diagram provides a gist of what Business Analytics is all about from the Enterprise perspective. Analytics helps in reducing the huge data that they have to getting valuable insights that allows them to take informed decisions.
Let me start with some background on what we all probably know Enterprise Data Warehouse. Basically data from variety of sources across the organization is collected and stored via ETL process of Extracting the data all across the enterprise, Transforming the data where by we only take relevant data and loading the data into the Data Warehouse.
The term BI / Reporting deals with Data Warehouse which allows businesses to slice and data from the Data Warehouse as well as run online queries to mine the data. This data is more structured and BI leverages past data to look at trends at macro level in different dimensions like geography, time, products, customers, stores, partners, campaigns etc.
Descriptive Analytics is a more recent term used instead of BI / Reporting this is more to do from a marketing perspective. Descriptive analytics focuses typically on past data to provide macro level summarization data as well provide answers to specific queries enabling business to understand itself better.
"What happened last quarter? Which BU Did well? "
The environment has changed tremendously due to digitization impact in terms of Mobility, Social and Cloud. In addition price of storage and compute has also come down dramatically.The data generated by organizations are huge and numerous data types, Enterprises need to be competitive and cannot just focus on past data but also need to be able created models that can forecast future behaviors. This is where Predictive Analytics comes into the picture.
Predictive Analysis allows organizations to create models that can leverage available data to provide data that is not available via Predictive Analytical Models.
"What will happen if this trend continues? What if analysis?"
To put things in perspective for example a retail enterprise may needs responses to the below questions grouped under Descriptive and Predictive analytics.
Descriptive :
- How much did Customer X spent in the last quarter?
- What are my top selling products?
Predictive :
- How much will Customer X will bring revenue by next 6 months?
- What could be the profitable products for my Gold customers that will bring in revenue in the next 6 months
Analytics has moved further from Predictive Analytics to a subset called Prescriptive Analytics where in addition to forecasting what could happen the model is able to predict consequences based on different choice of actions.
Below diagram summaries the differences between Descriptive, Predictive and Prescriptive analytics. Point to be noted is each is built on top of the other and complementary to each other.
The key challenge in Business Analytics is that Business does not understand the technical nuances of what and How Analytics is beneficial to them where as IT focusses on the technology to be developed and the algorithms to use rather then on Value to the Organization.
What is needed is a collaboration of Business and Analytics team to make there is a clearly defined Objectives of what is expected from business so accordingly the right Analytics strategy is put in place.