Companies are pushing for the use of the data they are collecting. The traditional method of data collection was data being stored in a data warehouse and reports were made about it for business teams. The data warehouse became a data silo, which means that anyone who wasn’t a technical user or understood SQL was only able to get information via dashboards and reports. These dashboards and reports were often general ideas of what was going on with the data, not including any more insights that could be beneficial for business decisions. However, the modern data stack is cloud based and can be accessed by more than just the data team. The modern data stack democratizes data and lowers the barrier for data integration. With this technology, business teams without a technical background can access these tools and use the data to produce profitable outcomes for the company. Looking at the modern data stack being used today, we can see what has been trending in 2022.
Are ETL and Reverse ETL The Same Thing?
Extract-transform-load (ETL) is moving data from a data source into a destination such as a data warehouse. This is necessary for your company to even collect data to work with. By copying data into your data warehouse, you then can use Reverse ETL to copy the data from the warehouse into commonly used business systems. These business systems are tools that your sales, marketing, finance, product, and support teams use to make crucial business decisions and create a better customer experience overall. They are not the same process, however both are necessary for collecting and using data within your business. You need ETL to copy data into the warehouse, and you need Reverse ETL to copy data from the warehouse to your business systems. These two categories in the modern data stack space are receiving data, eliminating data silos, and operationalizing data.
Why is Reverse ETL Trending?
Some people ask why Reverse ETL is part of the modern data stack trends of 2022. Reverse ETL eliminates having to build complex data pipelines and manage differing APIs. This makes copying data into business systems simple for anyone who knows basic SQL. It also integrates with other trending modern data stack tools, like dbt, to expose your source data and make it accessible for everyone who needs it.
Say Goodbye To Data Silos
At the beginning, moving data from systems into a centralized location was the main focus. But once it was moved, there was no development for how to actually leverage the data from that centralized location. This is how data silos are formed. All of this data is stored in one place, and only certain technical users can actually access the data. The only way to get the data out was to create complex data pipelines and understand APIs. This method can be costly, time consuming, and just a headache. That is why most companies don’t put in the effort to actually leverage their data for all its worth. Modern data stack tools, like Reverse ETL, have been developed to actually retrieve that data and put it to good use. Now, data can be aggregated, modeled, and enriched for business teams to use every single day.
Operational Analytics
Now that companies can easily move data from warehouses to business systems, operational analytics comes into play. Operational analytics is the process of analyzing data and using business systems to improve operations within a company. With data being enriched and put back into the business systems used by the company’s teams, they can make informed business decisions directly from the enriched and transformed data they have been given. This eliminates the creation of dashboards that no one uses, and makes data accessible right in the business tools teams use daily. When data is operationalized, it can be used to improve the efficiency of everyday operations.
Automated Updates
Even with a dashboard, there are still teams within a company that ask for CSV files of data or other pertinent information. This requires a member of the data team to manually write a SQL query and export the data as a CSV. Although this may seem like an easy task, it still kills the efficiency of the data team. With modern data stack, this process can be automated so the team doesn’t have to ask for certain numbers at the end of the month and the analyst doesn’t have to manually perform the task each time. Now, updates are automatically sent out to teams that require additional information and your data team has more time to focus on things that require their expertise.
2022 Data Trends
With the modern data stack leading the charge, companies are leveraging data like never before. With ETL copying data into a data warehouse, and Reverse ETL copying data into business systems, data is more accessible than ever. Business teams are able to operationalize their data, and the modern data stack is able to give automated updates to teams whenever they need it. Now businesses just need to jump on board and make the most of their data.
