Transform data engineering from a high-stress, “hero saves the day” kind of job into something systematic and predictable that actually scales as your team and business grow. Stop babysitting pipelines: SQL & ELT the FITT Way.
We’ve Been Using FITT Data Architecture For Many Years, And Honestly, We Can Never Go Back
Most data architectures are designed to maximize data vendor revenues, not data team productivity. Let us show you how a Functional, Idempotent, Tested, Two-Stage (FITT) data architecture can deliver better productivity, reliability, and happiness.
The DataOps Vendor Landscape, 2021
Download the 2021 DataOps Vendor Landscape here. Read the complete blog below for a more detailed description of the vendors and their capabilities. DataOps is a hot topic in 2021. This is not surprising given that DataOps enables enterprise data teams to generate...
Orchestrating StreamSets with the DataKitchen DataOps Platform
The cacophony of tools and mission-critical deliverables are the reason behind the high complexity of modern-day data organizations. Data groups include a wide range of roles and functions that are intricately woven together by their “Data”. Teams include data...
DataOps is Not Just a DAG for Data
We often hear people say that DataOps is just automating the data pipeline — using orchestration to execute directed acyclic graphs (DAGs). Enterprises may already use orchestration tools (Airflow, Control-M, etc.) and mistakenly conclude that they have DataOps...
