Data warehouse, intermediate platform, data lake and other technologies and solutions have laid a foundation for the use of modern enterprise data, especially the cloud of these platforms, so that these solutions become simple, highly available, so that the flow of data more quickly. Data warehouse and data middle office, call what is not important, the important is that they are in order to achieve the same goal, so their composition, and can be as simple as follows: the introduction to the data from multiple inward integrated into a core business system, after the data processing and backward integration to multiple outward from the core business system.

Whether a data warehouse or China, over the years we have always had a problem, that is what we solved the first half of the whole data system, and didn’t get the second half of the industry should pay attention to, so right now, we want to finish processing the data from the core of reverse integrated into various business system, is still resistance is big, obstacles. The current situation of this kind of hesitatness does not constitute a complete data system. The data is simply collected and processed, and there is no other use except to support some functions in products or produce BI reports. Obviously, our data application part is very simple.

Therefore, in order to make up the last link of this data system, we created jicheng homophonic “integration”, the first [reverse ETL] product in China. It can work on any major data warehouse or database, reverse-integrating data into the tools, platforms, and SaaS that each business depends on.

Let’s take a look at what reverse ETL is.

What is reverse ETL

From the last century to the present, our approach to data has changed very little, usually: multiple business systems -> ETL -> centralized storage. ETL is well known to all of us, so I will not elaborate too much. If I do not know ETL, I can search it by myself.

Reverse ETL, as the name implies, is: data center storage -> ETL -> multiple business systems.

Users through a reverse ETL, after processing can be user or product data storage such as a data warehouse or from the center database synchronization to where the business tools and platforms, such as constructed at pin guest, micro with aides, netease each guest on this type of CRM/SCRM, or tencent advertising, huge amounts of engine and other platforms, or marketing automation platform etc. Reverse ETL should have direct integration of common enterprise tools, platforms and SaaS as the data destination and common data warehouse/database as the data source, freeing engineering implementation and maintenance of synchronization between the data source and destination from the hands of the data team to automate and tool the whole process.

The last link in the data system

As I mentioned earlier, the lack of reverse ETL, or not doing enough of it, does not constitute a closed loop of the data system, so we often hear comments like “the data team does not have a presence” and “the data does not matter”.

Usually, a complete data system consists of the following major links:

  • Data integration: Commonly known as ETL/ELT, it is simply the integration of all business-relevant data from multiple systems into a central store.
  • Data store: A centralized storage that holds integrated data.
  • Data modeling: data processing and index production are completed through this link.
  • Data application: extremely achievement is specially for this link produced, so extremely become also called [data application automation].

Common usage scenarios for reverse ETL

The data itself is born to assist the business, and [reverse ETL] is to deeply integrate the processed data with the business to assist the business. It can be said that the scenarios are infinite. Here are some common scenarios:

  • Synchronize customer data to wechat companion assistant, so that private domain marketing based on a complete customer portrait
  • Use data automation to enjoy customer leads with products
  • Synchronize customer data to wisdom tooth customer service, make customer service efficiency fly
  • Report business indicators to nail group in real time
  • Using SQL to automatically update the mass engine crowd pack, enabling the marketing team to deliver Douyin and toutiao ads more accurately
  • Automated aurora push with customer portrait data

More scenes ->

Empower the data team

Reverse ETL gives the data team the ability to bypass the engineering team and directly support the business. The data team can directly use the data to automate various processes on marketing, sales, customer service, finance and other systems, and use the data to make others more efficient. The bottom line is that when companies get a taste for data, they pay more attention to the use of data. Digital transformation of enterprises depends partly on tools and partly on consciousness. We believe that if we minimize the difficulty of using tools, we will drive the use of data and thus change consciousness.

At present, the vast majority of our data is still only “with the eyes” level of use, but the use of data should not stop there, if you are interested in reverse ETL or data application automation, you can leave your contact information, our core members will contact you as soon as possible.