Remove Analytics Remove Data Lakes Remove DataOps
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Turnkey Cloud DataOps: Solution from Alation and Accenture

Alation

Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. DataOps has emerged as an exciting solution. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. Accenture’s DataOps Leap Ahead.

DataOps 52
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The Audience for Data Catalogs and Data Intelligence

Alation

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., ML and DataOps teams). After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that.

DataOps 52
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Popular Machine Learning Libraries, Ethical Interactions Between Humans and AI, and 10 AI Startups…

ODSC - Open Data Science

Automating Remediation Processes for Data Security Posture Management Before we look into how we can automate it, it is important to understand how data security posture management helps you achieve your goals.

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How HR Tech Company Sense Scaled their ML Operations using Iguazio

Iguazio

Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization including a large number of data and AI professionals. This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. First, the data lake is fed from a number of data sources.

ML 52
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How Sense Uses Iguazio as a Key Component of Their ML Stack

Iguazio

Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization, including a large number of data and data science professionals. This includes a data team, an analytics team, DevOps, AI/ML, and a data science team. Gennaro Frazzingaro, Head of AI/ML at Sense.

ML 52
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Fabrics, Meshes & Stacks, oh my! Q&A with Sanjeev Mohan

Alation

DataOps sprung up to connect data sources to data consumers. The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. The modern data stack depicts this whole loop of how the data is produced and consumed. Tools became stacks.

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Data Profiling: What It Is and How to Perfect It

Alation

Do you need to define a data quality rule and add that to the profile? Do you need to add metadata to information to put it in a data lake? Do you need to migrate data from one system to another? “Then based on the type of data, you can start asking questions.