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A Day in the Life of a DataOps Engineer

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?

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’

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

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...

How DataOps is Transforming Commercial Pharma Analytics

How DataOps is Transforming Commercial Pharma Analytics

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from...

Implementing a Pharma Data Mesh using DataOps

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...

Accelerating Drug Discovery and Development with DataOps

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

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

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?

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...

Using DataOps to Drive Agility & Business Value

Using DataOps to Drive Agility & Business Value

In May 2021 at the CDO & Data Leaders Global Summit, DataKitchen sat down with the following data leaders to learn how to use DataOps to drive agility and business value. Kurt Zimmer, Head of Data Engineering for Data Enablement at AstraZeneca Ryan Chapin, Former...

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