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Big Data Reference Architecture
We review your existing system and recommend data architecture per the industry best practices
Design Data Lakes
Most companies build data lakes that are tightly coupled with their compute. We help you avoid this and other pitfalls
Pre-Built Data Model Templates
We provide out of the box data engineering data models to turbo charge the development and customize for your use cases
Provide Technology Recommendation for Data Stack
Horses for courses. Right tech stack not only saves money but unlocks business potential across the enterprise
Root of all data engineering evil lies in the unnecessarily complex data processing pipeline
A Historical Primer
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Designing a data pipeline can be a serious business, building it for a Big Data based universe, however, can increase the complexity manifolds. The tools and concepts around Big Data started evolving around early 2000s as the size & speed of internet exploded. Companies suddenly found themselves having to deal with massive volumes & velocity of data. Arguably one of the pioneers in this field was Google where engineers were struggling with the search crawler & indexer, the piece of software that at the time underwrote Google’s search business and by extension the company. This arguably was the start of the big data revolution which continues to this day and the modern version is a juggernaut which needs to be tamed and not ignored
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