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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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Secrets from Data Governance Leaders: DGIQ West 2023 (June 5 – 9)

Alation

The Data Governance & Information Quality Conference (DGIQ) is happening soon — and we’ll be onsite in San Diego from June 5-9. If you’re not familiar with DGIQ, it’s the world’s most comprehensive event dedicated to, you guessed it, data governance and information quality. The best part?

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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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Data Catalog: Part of the Solution – or Part of the Problem?

Alation

Today a modern catalog hosts a wide range of users (like business leaders, data scientists and engineers) and supports an even wider set of use cases (like data governance , self-service , and cloud migration ). So feckless buyers may resort to buying separate data catalogs for use cases like…. Data governance.

DataOps 52
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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

Consequently, AIOps is designed to harness data and insight generation capabilities to help organizations manage increasingly complex IT stacks. It uses CI/CD pipelines to automate predictive maintenance and model deployment processes, and focuses on updating and retraining models as new data becomes available.

Big Data 106
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Data Profiling: What It Is and How to Perfect It

Alation

Top use cases for data profiling Data governance Data governance describes how data should be gathered and used within an organization, impacting data quality, data security, data privacy , and compliance. It can locate the ten things that may cause a problem instead of just one thing.

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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. Data mesh says architectures should be decentralized because there are inherent problems with centralized architectures.