Remove AI Remove Data Governance Remove DataOps
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How to Ensure Continuous Improvement With Data Governance

Alation

The goal of DataOps is to create predictable delivery and change management of data and all data-related artifacts. DataOps practices help organizations overcome challenges caused by fragmented teams and processes and delays in delivering data in consumable forms. So how does data governance relate to DataOps?

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9 data governance strategies that will unlock the potential of your business data

IBM Journey to AI blog

The best way to build a strong foundation for data success is through effective data governance. Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success.

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Alation Launches Data Governance App and Supporting Service Offering

Alation

The importance of data governance is growing. Here at Alation, we’ve seen the demand for new robust governance capabilities skyrocket in the past year. Alation Data Governance App. The Data Governance App introduces a range of new capabilities to make governance more easy and effective.

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The Audience for Data Catalogs and Data Intelligence

Alation

Over time, we called the “thing” a data catalog , blending the Google-style, AI/ML-based relevancy with more Yahoo-style manual curation and wikis. Thus was born the data catalog. In our early days, “people” largely meant data analysts and business analysts. ML and DataOps teams). data pipelines) to support.

DataOps 52
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Forging a Data Strategy for Success in Uncertain Times

Precisely

And they cite improved quality of data analytics and insights (57%) as the leading added value realized from data governance programs. They also report an increased focus on financial reporting and predictive analytics (28%) in response to the economic downturn.

DataOps 98
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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). However, they differ fundamentally in their purpose and level of specialization in AI and ML environments.

Big Data 106
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Data Integrity Trends for 2024

Precisely

In 2023, organizations dealt with more data than ever and witnessed a surge in demand for artificial intelligence use cases – particularly driven by generative AI. They relied on their data as a critical factor to guide their businesses to agility and success.