Welcome to Future: Generative Data Engineering

Leveraging Large Language Models to Automatically Build Data Lakes & Analytics Platform

Are You Ready to Accelerate Your Business?

Big Data Engineering is an exciting new domain unlocking huge potentials across Data Science, Analytics and Business Intelligence. Getting the right architecture and choosing an optimum tech stack makes all the difference between a successful implementation and a resource sink

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Data Architecure & Analytics Advisory

The age of big data has come with tremendous potential and huge challenges. We agree that building a data platform has never been so easy and yet fraught with so many wrong turns that you might end up further away from where you started.

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Data Migrations

We review your existing system and recommend migration strategies and architecture that works for you and results in significant cost saving

Accelerators

Data extracts, reports, dashboards - no matter what your need, we have AI driven accelerators to help to fullfill your committmets and significantly reduce time to market

Pre-Built Data Pipelines Templates

We provide out of the box data engineering pipelnes to turbo charge the development and customize for your use cases. Just bring your business needs

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

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