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Enhancing Data Fabric with SQL Asset Type in IBM Knowledge Catalog

IBM Data Science in Practice

In this blog, we explore how the introduction of SQL Asset Type enhances the metadata enrichment process within the IBM Knowledge Catalog , enhancing data governance and consumption. It enables organizations to seamlessly access and utilize data assets irrespective of their location or format.

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IBM to help businesses scale AI workloads, for all data, anywhere

IBM Journey to AI blog

Supporting the data management life cycle According to IDC’s Global StorageSphere, enterprise data stored in data centers will grow at a compound annual growth rate of 30% between 2021-2026. [2] ” Notably, watsonx.data runs both on-premises and across multicloud environments.

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How to Build a Successful Metadata Management Framework

Alation

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

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Bring Governance Bliss with Alation and Snowflake!

Alation

Data Governance is growing essential. Data growth, shrinking talent pool, data silos – legacy & modern, hybrid & cloud, and multiple tools – add to their challenges. They often lack guidance into how to prioritize curation and data documentation efforts.

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Data architecture strategy for data quality

IBM Journey to AI blog

Meaning, data architecture is a foundational element of your business strategy for higher data quality. Perform data quality monitoring based on pre-configured rules. Taking an inventory of existing data assets and mapping current data flows. Learn more about the benefits of data fabric and IBM Cloud Pak for Data.

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Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world

Pickl AI

This centralization streamlines data access, facilitating more efficient analysis and reducing the challenges associated with siloed information. With all data in one place, businesses can break down data silos and gain holistic insights.