9 Reasons why Business Intelligence and Database Developers should learn Machine Learning

Business Intelligence Insights can fuel Data Science Use Cases

1. BI will give you trends on historical data, BI will pin point what are your highlights and low lights
2. Effective Data Science use cases for Business will be converting this low lights into more proactive signs
3. BI will shed light on trend by seasonality, products, location etc. These values are effective feature variables for building your ML models

Database Developers are naturally good at Analyzing Data

I have worked with Terabyte of Data, Microsoft Entertainment and Devices data in 2008. I remember all the Insights we computed in Supply Chain, Orders, Returns, Warranty. When I started on Data Science I felt how those data can be effectively analyzed with Data Science

• Sales Analysis - The sales of products, regions, units sold can be clustered to find insights in it
• Repair Analysis - The types of products, repairs, regions can be clustered to find the most occurring issues
• Sales, Repair, Warranty renewal - From all the real time and Transactional data, we can build forecasting for repairs, sales, warranty renewal.

4. Database developers work with huge volumes of data, schema design, index design for performance

5. The Job involves aggregating, writing procedures to implement business transactions
6. Handling all load issues of concurrency, dead-lock, dirty data

These traits would be helpful setting up the data pipeline. All the work of generating insights can be achieved with TSQL itself. You do not really need to use pandas or learn from scratch

They can build pipelines, Reporting, Talk about the Numbers

7. Translate the insights / dimensions as feature variables
8. Communicate to business the insights and how they are data science use cases to solve
9. Naturally BI Reporting + Transactional Reporting will provide a lot of Visualization which also is a must for Data Science to present your story

Today Transactional Data Reporting, Business Intelligence Insights, Future predictions with Data Science everything is needed to succeed in business, OLTP + OLAP + Data Science = All about data in business

Note - I am not including Video, Text in this context. Data Science with Data (Numbers) is the scope of this post

#BusinessIntelligence, #MachineLearning, #Database. #TSQL, #ArtificialIntelligence, #DataPipeline

Happy Mastering Data Science!!!