DataKitchen

DECEMBER 7, 2021

If you can’t wait, check out this DataKitchen white paper, Build a Data Mesh Factory with DataOps. Practical DataOps: Delivering Agile Data Science at Scale , by Harvinder Atwal. Practical DataOps: Delivering Agile Data Science at Scale , by Harvinder Atwal. You can purchase Fail Fast, Learn Faster here. Author Laura B.

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DataKitchen

DECEMBER 30, 2020

While 2020 has been a collectively difficult year, we want to take a moment to thank all of our employees for the hard work they put into continually developing our DataKitchen DataOps Platform for our customers. Full disclosure: some images have been edited to remove ads or to shorten the scrolling in this blog post.

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Octopai

MAY 2, 2022

Data analytics ain’t what it used to be. It may not sound like such a big difference, but that switch affects your users’ expectations – and, therefore, what makes your data analytics team a productivity and profitability success. . Enter DataOps. What is DataOps? You’re providing data analytics products. .

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DataKitchen

AUGUST 9, 2021

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 team structure supports agility. DataOps Meta-Orchestration.

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DataKitchen

DECEMBER 9, 2022

Query> DataOps. ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

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DataKitchen

APRIL 26, 2021

In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva ; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK) ; and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise DataOps transformation journey, including key successes and lessons learned.

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DataKitchen

SEPTEMBER 17, 2021

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 successfully implementing a data mesh. How do you build a data factory?”

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DataKitchen

FEBRUARY 1, 2021

Every DataOps initiative starts with a pilot project. DataOps addresses a broad set of use cases because it applies workflow process automation to the end-to-end data-analytics lifecycle. DataOps reduces errors, shortens cycle time, eliminates unplanned work, increases innovation, improves teamwork, and more.

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DataKitchen

NOVEMBER 20, 2021

What makes an effective DataOps Engineer? A DataOps Engineer shepherds process flows across complex corporate structures. A DataOps engineer runs toward errors. You might ask what that means. A DataOps Engineer embraces errors and uses them to drive process improvements. Curating Processes.

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DataKitchen

JANUARY 20, 2021

As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. The beauty of DataOps is that you don’t have to choose between centralization and freedom. DataOps Technical Services. DataOps Center of Excellence. DataOps Dojo .

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DataKitchen

APRIL 28, 2021

Forrester relates that out of 25,000 reports published by the firm last year, the report on data fabrics and DataOps ranked in the top ten for downloads in 2020. What is a Data Fabric? Gartner included data fabrics in their top ten trends for data and analytics in 2019. This is happening to the term “data fabric.”

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DataKitchen

JANUARY 6, 2021

As data professionals, we know the value and impact of DataOps: streamlining analytics workflows, reducing errors, and improving data operations transparency. Being able to quantify the value and impact helps leadership understand the return on past investments and supports alignment with future enterprise DataOps transformation initiatives.

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DataKitchen

AUGUST 13, 2021

Pharmaceutical companies are finding that DataOps delivers these benefits. DataOps automation provides a way to boost innovation and improve collaboration related to data in pharmaceutical research and development (R&D). Figure 2 illustrates a self-service DataOps Platform for scientists engaged in pharmaceutical R&D.

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DataKitchen

NOVEMBER 4, 2021

DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. The requirement to integrate enormous quantities and varieties of data coupled with extreme pressure on analytics cycle time has driven the pharmaceutical industry to lead in DataOps adoption. The Last Mile Problem.

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DataKitchen

JANUARY 3, 2022

Instead of throwing people and budgets at problems, DataOps offers a way to utilize automation to systematize analytics workflows. DataOps consolidates processes and workflows into a process hub that curates and manages the workflows that drive the creation of analytics. In business analytics, fire-fighting and stress are common.

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DataKitchen

SEPTEMBER 20, 2021

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 steps. In short, Lean DataOps is the fastest path to DataOps value.

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DataKitchen

AUGUST 19, 2021

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. Figure 3: Example DataOps architecture based on the DataKitchen Platform. The data scientists and analysts have what they need to build analytics for the user.

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DataKitchen

AUGUST 5, 2021

Last we’ll explore how DataOps can be paired with data mesh to mitigate these challenges. Customers are on a journey to get insight, and they may not know exactly what they want until they see it. If you still have difficulty understanding the concept of the data mesh design pattern, please see our recent post “ What is a Data Mesh? ”.

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DataKitchen

JUNE 24, 2021

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. DataOps is a Key Enabler of Business Agility. DataOps can mean different things to different organizations. DataOps is a complementary process.

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DataKitchen

MAY 10, 2021

If you have been in the data profession for any length of time, you probably know what it means to face a mob of stakeholders who are angry about inaccurate or late analytics. Data Observability Component of DataOps. DataKitchen has developed a methodology implemented around our DataOps Platform to reduce data errors to virtually zero.

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DataKitchen

NOVEMBER 18, 2021

For see the entire results of the data engineering survey, please visit “ 2021 Data Engineering Survey: Burned-Out Data Engineers are Calling for DataOps.”. In addition, only one-third of companies have an established CDO role, and the average tenure of the CDO is only 2.5 Data engineers end up fixing the same problem over and over.

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DataKitchen

JANUARY 25, 2021

What happened? DataOps uses automation to create unprecedented visibility into data operations. Below we’ll show an actual report used by a DataOps enterprise. It helps people keep their “finger on the pulse” of what is happening, so stakeholders started calling it the “Pulse Report.”. The Pulse Report.

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DataKitchen

MAY 2, 2025

More often, it’s baked into team culture, shaped by tools that don’t make quality visible, roles that lack ownership, and a lack of shared language to even talk about what’s broken. Ask your team what it means to take ownership of data quality. Is Your Team in Denial of Data Quality? Is your team ready? Interested?

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DataKitchen

SEPTEMBER 18, 2024

A DataOps Approach to Data Quality The Growing Complexity of Data Quality Data quality issues are widespread, affecting organizations across industries, from manufacturing to healthcare and financial services. The DataOps methodology offers a solution by providing a structured, iterative approach to managing data quality at scale.

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DataKitchen

MAY 10, 2021

After establishing a solid strategy, the second phase involves planning key processes and practices to support the strategy, including “the emerging and increasingly important DataOps and ModelOps processes and methodologies.”. Blog: What is DataOps ? White Paper: DataOps is Not Just DevOps for Data .

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DataKitchen

MARCH 11, 2021

Gartner identified XOps (DataOps, ModelOps, DevOps) as one of the top trends in data and analytics for 2021. What is XOps? . DataKitchen Blog: Why Are There So Many *Ops Terms? DataKitchen White Paper: DataOps is NOT Just DevOps for Data. DataKitchen Blog: Improving Teamwork in Data Analytics with DataOps.

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DataKitchen

AUGUST 3, 2021

A DataOps superstructure provides the foundation to address the many challenges inherent in operating a group of interdependent domains. DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . But first, let’s define the data mesh design pattern. The problem is not “you.”

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DataKitchen

DECEMBER 6, 2022

We are excited that Gartner released its ‘Market Guide to DataOps’ ! The document they wrote is exceptionally close to what we see in the market and what our products do ! This document is essential because buyers look to Gartner for advice on what to do and how to buy IT software. What is missing?

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DataKitchen

OCTOBER 5, 2022

This is the first post in DataKitchen’s four-part series on DataOps Observability. DataOps Industry Challenges. DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Part 1: Defining the Problems. Errors Happen; Do You React or Prevent?

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DataKitchen

FEBRUARY 21, 2023

What is Gartner’s advice for a new data engineering lead like Marcus? Adopt DataOps Practices : “Successful data engineering teams are cross-functional and adopt DataOps practices.” Data team morale is consistent with DataKitchen’s own research. It’s not been going well. A better ETL tool? Pick some other hot tool?

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DataKitchen

DECEMBER 20, 2020

The Role of DataOps and the DataOps Engineer. Within the data industry, this effort is called DataOps , and it is implemented by someone called a DataOps Engineer. If you want to attain greater business agility through faster, more responsive data analytics, then the DataOps Engineer should be your first hire.

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DataKitchen

JUNE 7, 2021

The primary source of information about DataOps is from vendors (like DataKitchen) who sell enterprise software into the fast-growing DataOps market. There are over 70 vendors that would be happy to assist in your DataOps initiative. What can you do? DataOps is not an all-or-nothing proposition.

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DataKitchen

FEBRUARY 4, 2021

This blog builds on earlier posts that defined Kitchens and showed how they map to technical environments. DataOps automates the source code integration, release, and deployment workflows related to analytics development. Aside from the actual creation of new analytics and associated tests, DataOps orchestrates all of the above.

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DataKitchen

JANUARY 5, 2021

The disparate toolchains illustrate how each group resides in its own segregated silo without an ability to easily understand what other groups are doing. In the data analytics market, this endeavor is called DataOps. Data Governance/Catalog (Metadata management) Workflow – Alation, Collibra, Wikis.

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DataKitchen

AUGUST 16, 2024

2024 Gartner Market Guide To DataOps We at DataKitchen are thrilled to see the publication of the Gartner Market Guide to DataOps, a milestone in the evolution of this critical software category. DataOps is at the intersection of many different product categories.

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Alation

SEPTEMBER 28, 2022

What exactly is DataOps ? This is nothing new, as 74% of respondents indicated that new compliance and regulatory requirements have accelerated the adoption of DataOps (IDC). This is nothing new, as 74% of respondents indicated that new compliance and regulatory requirements have accelerated the adoption of DataOps (IDC).

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DataKitchen

SEPTEMBER 21, 2023

What is Data in Place? Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. What is Data in Use? One of the primary sources of tension? There are multiple locations where problems can happen in a data and analytic system.

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