Thursday, October 6, 2016

Business Intelligence VS Data Science

just ask any practitioner within the field and you will notice at first, the answers appeared to be a random mix, but once they were collated and reviewed, there was a general consensus.

Some of the more in-depth answers included

“Data Science is the core for BI; it is the one in charge of developing the algorithms and strategies to data patterns and trends in data. Business Intelligence uses what Data Science produces in order to give enterprise value to its information.”

“BI is more of a decision support system which helps business drive focus while Data Science is more statistics-driven, and we need folks to pay more attention to granularities within the data. BI is more about ETL and dashboards presentation while Data Science is more focused on finding anomalies within data and establishing the pattern.”

Data Science generates insights and finds anomalies in data, scans, and predicts the future. BI helps to see where your business is at a point in time, generates reports, and dashboards. It is limited to past and present.”

“To me Data Science sounds like the study of making use of data to enable and optimize the realization of information knowledge from it. Business Intelligence makes me think of moving transactional data to a Data Warehouse and writing reports from there. But maybe that isn’t all that different.”

Type of question BI systems can answer .


  • How many customers have visited our website every day for the past five years?
  • What is product X’s revenue trend over the holidays?
  • How often do we need to replace a particular part on our assembly line?
  • What has been our most successful sales campaign based on certain metrics?
  • What is the historical water usage during summer months of our customers in a given locale?
  • Who are our most valuable customers?
  • How many page views did we get from a given article last month?
  • What is our total inventory stock of agiven item?

Type of questions Data Science allow you to answer 


  • How many customers will visit our website next month and buy something rather than just click through?
  • Based on their past behaviors, which customers are most likely to be interested in our new product Y?
  • What correlations exist among season, geographical region, certain product lines, and a given social media campaign when looking at why a customer will purchase a product versus just browse our product listings?
  • What variables will make our next marketing campaign the most successful?
  • What variables make one patient more likely to have a given medical condition over other patients?Which medical treatments and preventative measures are most successful in helping such conditions?
  • How can we use geo-location data with real-time weather patterns to figure out how best to route incoming and outgoing planes?
  • What can the combination of historical flooding data and remote maintenance sensors data tell
  • us about creating preemptive flood overflow plans for our most problematic city neighborhoods?
Over the next 5 years do you plan to invest in Predictive Analytics (BigData/Data Science)?”