Often, we find that a client needs to organize its data properly to get started on analytics and AI.
Thus, before we rush into lofty matters, let’s collect all data inside the centralized warehouse, unify and automate ETL pipelines to keep the data consistent and updated in time.

Why would you want to organize your data?

Proper data management is a long-term investment.
It pays off generously on a months and years scale in the forms of:

  • Significant reduction in manual toil.
    Your resources will be able to focus on valuable business goals rather than manually running SQL queries.
    Wait, your Data Scientists still do that instead of their direct responsibilities?
    You’re wasting your money!
  • Consistent data sources and consistent reports & charts.
    Remember that budget report you showed in May?
    And how your colleagues in California showed other numbers.
    Yep, quite a situation.
    And all due to the scattered data sources and eventual consistency.
  • Simplification & time savings of working with one data source.
    Does your DBA department spend 90% of time customizing queries to assemble the data every month?
    Congrats, you’re wasting money.

These are only a few core benefits.

Every organization, sooner or later, meets the need to organize and process its data properly.

DATA PIPELINES DATA SOURCES Web Database File FTP Groomed for analytics and AI Preprocessed Unstructured DATA WAREHOUSE DATA PIPELINES DATA SOURCES Web Database File FTP DATA WAREHOUSE

Data Sources

Working with data from disparate data sources is a waking nightmare.

Some of your databases are on local servers; some – on cloud-managed services. There is a portion of the data in the form of flat files on FTP servers. And there is a guy dedicated to making dumps manually from public government websites weekly. Also, there is information stored on your employee’s home PC without access to the enterprise intranet. The employee copies it to a USB flash card, walks to the office, and uploads it to an FTP drive.

Sounds familiar?
(by the way, the story is accurate)
Does it look effective?

Data Pipelines

A set of pipelines that reaches the sources may be triggered by an event or follow the predefined schedule. ETL pipelines automatically perform necessary transformations and load the transformed data into the warehouse.

Data Warehouse

Data warehouse is a persistent, secure, enterprise-grade storage for the groomed data that have been extracted and transformed on the ETL stage.

Optimized for fast data recording.
Or for fast reading.
Or for both — depending on your needs.