DataKitchen

AUGUST 24, 2023

Since the first edition of the DataOps Cookbook in 2019, we have talked with thousands of companies about their struggles to deliver data-driven insight to their customers. The DataOps Cookbook-‘Data Journey First DataOps’ Third Edition is the answer to that challenge.

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Data Analytics Systems Process Building 52

DataKitchen

FEBRUARY 23, 2024

DataKitchen Resource Guide To Data Journeys & Data Observability & DataOps Data (and Analytic) Observability & Data Journey – Ideas and Background Data Journey Manifesto and Why the Data Journey Manifesto? Five Pillars of Data Journeys Data Journey First DataOps “You Complete Me,” said Data Lineage to Data Journeys.

Data Validation 48

Data Validation Data Data Pipeline Data Solutions 48

Data Engineering Podcast

MARCH 18, 2019

DataOps is a set of practices to increase the probability of success by creating value early and often, and using feedback loops to keep your project on course. Summary Delivering a data analytics project on time and with accurate information is critical to the success of any business.

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Data Lake Machine Learning Manufacturing Deep Learning 100

DataKitchen

JANUARY 2, 2021

This is similar to findings in a joint Eckerson-DataKitchen DataOps survey. In this report, Gartner outlines recommendations to effectively operationalize AI solutions that involve the core management competencies of ModelOps, DataOps, and DevOps. Figure 1: Operational AI Requires ModelOps, DataOps, and DevOps Practices.

Data Engineering 52

Data Engineering Data Engineer Engineering Government 52

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. A DataOps Engineer transforms the picture above to the automated factory below (figure 2). You might say that DataOps Engineers own the pipelines and the overall workflow, whereas data scientists and others work within the pipelines.

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Engineering Raw Data SQL Data Engineering 62

DataKitchen

OCTOBER 28, 2021

Addressing AI Bias With DataOps. Engineers unleashed artificial intelligence (AI) bias, and it will be engineers who design the solutions that eliminate it. That’s an important start. The industry can also adopt a proactive, process-oriented approach to addressing AI bias. What Is AI Bias?

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Coding IT Manufacturing Algorithm 52

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. DataOps is not an all-or-nothing proposition. DataOps Objectives.

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Coding IT Data Pipeline Data Analytics 52