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Summary of the Gartner Presentation: “How Can You Leverage Technologies to Solve Data Quality Challenges?”
Summary of the Melody Chien from Gartner Presentation: “How Can You Leverage Technologies to Solve Data Quality Challenges?”
Drug Launch Case Study: Amazing Efficiency Using DataOps
When launching a groundbreaking pharmaceutical product, the stakes and the rewards couldn’t be higher. This blog dives into the remarkable journey of a data team that achieved unparalleled efficiency using DataOps principles and software that transformed their analytics and data teams into a hyper-efficient powerhouse.
Eight Top DataOps Trends for 2022
DataOps adoption continues to expand as a perfect storm of social, economic, and technological factors drive enterprises to invest in process-driven innovation. From our unique vantage point in the evolution toward DataOps automation, we publish an annual prediction...
How To Succeed as a DataOps Engineer
What makes an effective DataOps Engineer? A DataOps Engineer shepherds process flows across complex corporate structures. Organizations have changed significantly over the last number of years and even more dramatically over the previous 12 months, with the sharp...
10 DataOps Principles for Overcoming Data Engineer Burnout
For several years now, the elephant in the room has been that data and analytics projects are failing. Gartner estimated that 85% of big data projects fail. Data from New Vantage partners showed that the number of data-driven organizations has actually declined to...
Centralize Your Data Processes With a DataOps Process Hub
Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization...
What Is ‘Equity As Code,’ And How Can It Eliminate AI Bias?
This article was originally published in Forbes. Engineers unleashed artificial intelligence (AI) bias, and it will be engineers who design the solutions that eliminate it. Authors of an article published by McKinsey Global Institute assert that “more human vigilance...
Infographic – Data Engineers are Burned Out and Calling for DataOps
A survey commissioned by data.world and DataKitchen reveals a disturbing state of affairs among data engineering professionals. The study of 600 data engineers, conducted by Wakefield Research, suggests an overwhelming majority are burned out and calling for relief....
A Day in the Life of a DataOps Engineer
A DataOps implementation project consists of three steps. First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of...
What is a DataOps Engineer?
A DataOps Engineer owns the assembly line that's used to build a data and analytic product. Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output...
Start DataOps Today with ‘Lean DataOps’
Data organizations don’t always have the budget or schedule required for DataOps when conceived as a top-to-bottom, enterprise-wide transformational change. An essential part of the DataOps methodology is Agile Development, which breaks development into incremental...
DataOps is the Factory that Supports Your Data Mesh
Below is our final post (5 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a data mesh decentralized architecture. We see a DataOps process hub like the DataKitchen Platform playing a central supporting role in...
Implementing a Pharma Data Mesh using DataOps
Below is our fourth post (4 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a decentralized architecture. We’ve covered the basic ideas behind data mesh and some of the difficulties that must be managed. Below is a...
