Reverse ETL

Business Analytics has been the most demanding cycle in the current era. Business Analytics supports DSS (Decision Support Systems) and the technologies to support started from OLTP systems to OLAP systems i.e., source systems to Data Warehouses or Data Marts or Data Lakes or Data Lake Houses or Data Vault or Business Vault or Enterprise Data Hubs or Enterprise Data Fabric etc., but that’s not the complete cycle. The cycle completes once Reverse ETL is performed.

Let’s understand with an example. For example, the product sales data is loaded in a system (OLTP) then it is pushed or pulled in a Data Lake or a Data/ Business Vault or in a Data Warehouse or Data Mart or Data Lake House etc. Once data has move in these datastores then analytics are performed using Data Science practice like by running Machine Learning, Deep Learning, and many other means to analyze data for prediction or forecasting and last but not the least the data is present to Top Management for decision marking. Management decides to initiate campaigns based on the data element extracted from the whole cycle from OLTP to OLAP etc.

Most of us thinks the cycle is completed at this junction but that’s not correct, STORY ABHI BAKI HAI DOSTOON 😊 (a light joke for those who understand URDU language).

In the current era, most of the data is generated from social media. Considering, we pull all kinds of data from social media and never write backs. Yes, writing back to social media into the format it accepts is Reverse ETL. This example might not have excited you. Let’s take another example.

Referring to the same example mentioned above, the product is sold, and data travelled from multiple datastores to top management. Now, when management takes a decision to initiate a campaign and give some discount, it’s not only about sending messages to customers’ mobile. The cycle ends by sending out the output of the campaigns to source systems. When the customer representative opens the system to initiate a new sale, the representative can see that a campaign was sent to this buyer’s mobile but the buyer never reaction to that. Now, sales representative can remind the buyer that you didn’t make use of that campaign and can offer another discount by saying, ‘if you want to make use of the campaign, please buy US100 more and you will get 30% (just as an example) discount on the whole bill.’

Hope we understand the importance of Reverse ETL. Please note, Reverse ETL is not only about copy pasting the Analytics output in source system. Each source system has its own OLTP data model, Reverse ETL must follow the same data model before writing back.