Remember that online newspaper or magazine subscription you purchased and promised to read daily but never did? Your email is now cluttered with great information, but you barely have the time to read through it. This sums up the situation regarding data. Due to the enormous amount of data being generated, many companies cannot make the best use of it. Managing these considerable data volumes is daunting, and businesses may never use some of them. The cost of this, however, is companies miss out on the ability to generate priceless insights about their business.
However, to go back to our subscription example, what if your magazine was integrated with your social media account? You could click on it while scrolling through your Instagram feed and skim through articles, making more use of the subscription rather than letting it sit in your inbox. Similarly, what if there was a way to feed your stored data into business applications and use it in various functions? This is where reverse ETL comes in.
Breaking down data silos with reverse ETL software
Reverse ETL (extract, transform, and load) helps to operationalize data. This means that using reverse ETL tools helps break down data silos and ensures teams in an organization have access to clean, high-quality data to drive well-informed business decisions. With these tools, any team within an organization has the power to access the data they need to make decisions. Reverse ETL is used to power workflows and provide clean, processed data, one of the use cases being marketing and advertising campaigns.
Reverse ETL (extract, transform, and load) is the process of syncing data from data warehouses to several business applications. Reverse ETL software pulls data from data warehouses. It sends this data to SaaS tools, third-party integrations, and pre-built connectors, which can then be used by marketing, sales, and customer support teams.
ETL tools extract data from data sources, transform them into a digestible format, and then load them into a data warehouse. ELT tools extract data, load it into the warehouse and only then transform the data into a digestible format. Reverse ETL tools, however, invert the ETL process, considering data is moving out of the data warehouse and into several business applications. The image below best illustrates the differences between these tools.
Last mile delivery software would be a good example to visualize the reverse ETL process. In last mile logistics, products are delivered from a distribution center or a warehouse to the customer. In the case of reverse ETL, the product being delivered is data, and it is moved from a data warehouse (the distribution facility or warehouse) to different teams in an organization (the customer).
| Let’s look at some use cases of reverse ETL: |
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Why should I know about reverse ETL? Is it the right fit for me?
Companies analyze data through visualizations and dashboards. Many business intelligence and analytics tools are available that help companies make the best decisions from their data. This is the best approach to identifying insights, but imagine having all this data fed back into customer, sales, and marketing tools. Companies would be able to use that data to better the customer experience. This data can help improve products, personalize customizations, and build a brand's personal touch. It helps a company focus on the future, not just on analyzing historical data.
You can identify the key players in the newly added Reverse ETL category with the G2 Grid®.
| Read more: G2 Fall 2022 Reports: Insights Gleaned from 13,057 Software Products → |
Integrations are the future
Integrations are the unique selling point (USP) of reverse ETL software. Although reverse ETL is gaining popularity, the usage of reverse ETL tools depends on its integrations with other SaaS tools, which help the users make the best use of it. Most reverse ETL tools connect to data warehouses such as Amazon RedShift and Snowflake and sync it with business applications. We expect to see several reverse ETL vendors updating their integrations to support numerous teams, such as sales, marketing, customer service, finance, and product teams.
Edited by Shanti S Nair
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Preethica Furtado
Preethica is a Market Research Manager at G2 focused on the cybersecurity, privacy and ERP space. Prior to joining G2, Preethica spent three years in market research for enterprise systems, cloud forecasting, and workstations. She has written research reports for both the semiconductor and telecommunication industries. Her interest in technology led her to combine that with building a challenging career. She enjoys reading, writing blogs and poems, and traveling in her free time.
