Blog
What Does Flossing One Tooth Have to Do with Data Quality?
Surprisingly, the answer may comes from an unusual place.
“Trusting Your Gut” 78.45% More Effective Than Data-Driven Decisions
Gartner/Harvard study: “Fire your data team tomorrow” and replace data and analytic teams with “affirmative decision AI agents”
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...
A Day in the Life of a DataOps Engineer
Accelerating Drug Discovery and Development with DataOps
A drug company tests 50,000 molecules and spends a billion dollars or more to find a single safe and effective medicine that addresses a substantial market. Figure 1 shows the 15-year cycle from screening to government agency approval and phase IV trials. Drug...
Addressing Data Mesh Technical Challenges with DataOps
Below is our third post (3 of 5) on combining data mesh with DataOps to foster greater innovation while addressing the challenges of a decentralized architecture. We’ve talked about data mesh in organizational terms (see our first post, “What is a Data Mesh?”) and how...
Use DataOps With Your Data Mesh to Prevent Data Mush
In our last post, we summarized the thinking behind the data mesh design pattern. In this post (2 of 5), we will review some of the ideas behind data mesh, take a functional look at data mesh and discuss some of the challenges of decentralized enterprise architectures...
What is a Data Mesh?
The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. With an architecture comprised of numerous domains, enterprises need to manage order-of-operations issues, inter-domain...
