How Reverse ETL Can Improve Data Enrichment?

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As a concept, data enrichment should be a part of every presently active company. Data enrichment is simply enriching data that allows companies to confidently use their accumulated data to make business decisions that could positively impact their financial performance.

But because as quickly as companies collect their data, data can change. Data enrichment as a practice helps to keep data up to date. Reverse ETL is one of the data processes companies employ in order to maximize the data in their possession.

But what is reverse ETL? As a matter of fact, what is ETL and why do companies need the options of both in order to truly get the most of the data in their possession? 

What Is ETL?

ETL is short for Extract, Transform and Load. This is the process of aggregating from various sources. It then transforms the data according to that company’s rules and loads the data into a destination data store. 

It was after 1970 that preserving databases really got popular with companies across the globe, ETL was introduced as a process for loading data for computation and analysis. 

It takes place in the three steps mentioned previously: 

Extract – where data is collected from one or more data sources. It is then held in temporary storage until it is ready for the upcoming steps; Transform – the transformation phase is where the data extracted is processed to make its values and structure conform consistently with its intended use case. The goal of transformation is to make all data fit within a uniform database until the last step; Load – the load phase moves the transformed data into a permanent target system. This could be a target database, data warehouse, data store, data hub or on-premises, or in the cloud. Once all the data has been loaded, the process is complete. 

Now that was fine for most companies for quite some time however as a modern data stack became adapted across the board. More was required from a company’s database. So the need came for regular systems to be altered instead of data from many data sources being brought into a central warehouse and staying there. While there are times when data needs to be extracted from the data warehouse and pushed into third-party end systems. This process has been dubbed reverse ETL. And has become more popular as time has gone on, reverse ETL emerged out of the necessity to get data and insights from a company’s warehouse back into the hands of the teams who dealt directly with customers. In order to avoid unwanted data decay. That being said, what does all of that mean for the company and its customer base, and what part does reserve ETL play in maximizing company data? 

How Does Reserve ETL Work To Enrich Company Data?

Company departments like sales, marketing, production, support, and analytics, could all benefit from the same, consistent, and reliable data. Reverse ETL  allows access to data across different departments. The only limits are the restrictions a company may set for privacy and security reasons.

As a result, data silos – insular management systems in which one information system or subsystem is incapable of reciprocal operation with others – break down, and there is no longer a need for a team to keep begging another team or a data analyst to create a list or report. With reverse ETL there are four primary usages to enhance company data: 

  • Data intelligence – to integrate the data warehouse with the business intelligence (BI) tool to analyze the data for decision and BI support. This helps data scientists and business analysts employed by the company to see complete views of the data required for forecasting and planning.
  • Data formats – because different user personas and departments are expected to represent the data in different formats based on their requirements. Reverse ELT is required to ensure that the file formats are available in the ways they need to be.
  • Source ecosystems – Every organization uses multiple applications to address their day-to-day business use cases. With reverse ETL, companies can now move the data from the warehouse to applications and tools to run the business processes easily and effectively. 
  • Enhancing Customer Experiences – unleveraged data from data warehouses becomes accessible and available with reverse ELT in real time. This could be utilized to offer the right solution to the right customer at the right time, improving the overall customer experience.

Once a reverse ETL tool is connected to a company’s data warehouse, there will be a reduction in the need for data analysts to manually extract and prepare data. Analysts face many requests like these every day, which means they can spend hours performing a relatively simple task over and over again. Wasting company time and money.

Implementing a reverse ETL tool saves data teams a lot of time and lets them focus on solving more complex data problems, such as maintaining a high quality of data, implementing security and privacy practices, and identifying the most useful metrics and information for a company’s goals and problems.

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