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Improving Data Pipelines with DataOps

Dataversity

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

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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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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

The data universe is expected to grow exponentially with data rapidly propagating on-premises and across clouds, applications and locations with compromised quality. This situation will exacerbate data silos, increase pressure to manage cloud costs efficiently and complicate governance of AI and data workloads.

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Data Integrity Trends for 2024

Precisely

They’re where the world’s transactional data originates – and because that essential data can’t remain siloed, organizations are undertaking modernization initiatives to provide access to mainframe data in the cloud.

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Demystifying Data Mesh

Precisely

Even without a specific architecture in mind, you’re building toward a framework that enables the right person to access the right data at the right time. However, complex architectures and data silos make that difficult. It’s time to rethink how you manage data to democratize it and make it more accessible.

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

IBM Journey to AI blog

Master data management (MDM) MDM tools keep an organization’s master data—such as customer, product or supplier information—consistent and up-to-date across systems and departments, preventing data silos and providing a unified view of critical data entities.

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

Alation

So feckless buyers may resort to buying separate data catalogs for use cases like…. Data governance. For example, the researching buyer may seek a catalog that scores 6 for governance, 10 for self-service, 4 for cloud data migration, and 2 for DataOps (let’s call this a {6, 10, 4, 2} profile). Self-service.

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