Data synchronization for high-load CRM system

About project:

Client overview

A data analytics company needed an efficient solution for their frequent data export requirements from profile tables. The manual process of writing SQL queries for each export request was time-consuming and resource-intensive, impacting their operational efficiency and team productivity.

Tech Stack:

Manual scripts and query writing

Tech stack after migration:

Automated python scripts, Airflow DAGs

Time to deliver project:

4-6 Weeks

Problem

  • The client frequently needed to export data from the profile table with various columns and filters. Writing a new query each time was cumbersome and took up valuable working hours.

Inspection

  • We developed a script that accepts a list of column names and filter descriptions as parameters. It also allows the user to choose the output format (CSV or Excel) and whether to export the data in a single file or multiple files. This streamlined the process from writing complex SQL queries to simply providing a list of parameters in the configuration. The exports are automatically sent to a designated Slack channel in the required format, ready to be shared with the customer.

Recommendation

  • Consider expanding this automation to other frequently accessed tables or data sets. Additionally, integrating an API to trigger these exports on-demand from external systems could further enhance operational efficiency.

Resolution

We automated the export process for profile data. This solution reduced the time spent on manual query writing by over 80%, increased flexibility in data export, and ensured that exports were consistently formatted and delivered quickly. The new system has allowed the team to focus on more strategic tasks, significantly boosting productivity.

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