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Five Important Trends in Big Data Analytics

Flipboard

Over the last few years, with the rapid growth of data, pipeline, AI/ML, and analytics, DataOps has become a noteworthy piece of day-to-day business New-age technologies are almost entirely running the world today. Among these technologies, big data has gained significant traction. This concept is …

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DataOps vs. DevOps: What’s the Difference?

Alation

DataOps and DevOps are two distinctly different pursuits. But where DevOps focuses on product development, DataOps aims to reduce the time from data need to data success. At its best, DataOps shortens the cycle time for analytics and aligns with business goals. What is DataOps? What is DevOps? The Agile Connection.

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What Is DataOps? Definition, Principles, and Benefits

Alation

What exactly is DataOps ? The term has been used a lot more of late, especially in the data analytics industry, as we’ve seen it expand over the past few years to keep pace with new regulations, like the GDPR and CCPA. In essence, DataOps is a practice that helps organizations manage and govern data more effectively.

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Turnkey Cloud DataOps: Solution from Alation and Accenture

Alation

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. As pressures to modernize mount, the promise of DataOps has attracted attention. People want to know how to implement DataOps successfully.

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Take the Route to AI Success with DataOps and MLOps

DataRobot Blog

The survey asked companies how they used two overlapping types of tools to deploy analytical models: Data operations (DataOps) tools, which focus on creating a manageable, maintainable, automated flow of quality-assured data. If deployment goes wrong, DataOps/MLOps can even help solve the problem. Survey Questions.

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Forging a Data Strategy for Success in Uncertain Times

Precisely

For the report, more than 450 data and analytics professionals worldwide were surveyed about the state of their data programs. Half of the respondents (50%) say their strategies are influenced by advanced data analytics, a critical technology for amplifying data-driven decision-making. One major finding?

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The Audience for Data Catalogs and Data Intelligence

Alation

ML and DataOps teams). Power business users and other non-purely-analytic data citizens came after that. analysts, data scientists, compliance, stewards, data engineers, analytics engineers ) executing multiple use cases (e.g., At one level, it makes sense – there is certainly a lot of interest in DataOps today.

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