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The Missing Link in Enterprise Data Governance: Metadata

Octopai

Why aren’t the numbers in these reports matching up? We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” In a panic, he went from desk to desk asking his teammates if they had been working on the same reports that day. They deal with tens if not hundreds of reports each day….

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Do I Need a Data Catalog?

erwin

The data catalog is a searchable asset that enables all data – including even formerly siloed tribal knowledge – to be cataloged and more quickly exposed to users for analysis. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata. for analysis and integration purposes).

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Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. On the other hand, data lakes are flexible storages used to store unstructured, semi-structured, or structured raw data.

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Making OT-IT integration a reality with new data architectures and generative AI

CIO Business Intelligence

Legacy data management is holding back manufacturing transformation Until now, however, this vision has remained out of reach. Industrial knowledge graphs employ industry-standard metadata to contextualize and structure data so it can be used in large language models.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

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Why You Need End-to-End Data Lineage

erwin

Yet given this era of digital transformation and fierce competition, understanding what data you have, where it came from, how it’s changed since creation or acquisition, and whether it poses any risks is paramount to optimizing its value. Data Lineage Tells an Important Origin Story. Who are the data owners?

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What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

Data scientists often work with data analysts , but their roles differ considerably. Thus, the difference between the work of data analysts and that of data scientists often comes down to timescale. The data that data scientists analyze draws from many sources, including structured, unstructured, or semi-structured data.