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What is data governance? Best practices for managing data assets

CIO Business Intelligence

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

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8 data strategy mistakes to avoid

CIO Business Intelligence

“Establishing data governance rules helps organizations comply with these regulations, reducing the risk of legal and financial penalties. Clear governance rules can also help ensure data quality by defining standards for data collection, storage, and formatting, which can improve the accuracy and reliability of your analysis.”

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The Rise of Unstructured Data

Cloudera

In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. Data curation.

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AI Adoption in the Enterprise 2021

O'Reilly on Data

The biggest problems in this year’s survey are lack of skilled people and difficulty in hiring (19%) and data quality (18%). The biggest skills gaps were ML modelers and data scientists (52%), understanding business use cases (49%), and data engineering (42%). Bad data yields bad results at scale. form data).

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Data migration to Snowflake, a comprehensive primer

Octopai

This can be more cost-effective than traditional data warehousing solutions that require a significant upfront investment. Support for multiple data structures. Unlike traditional data warehouse platforms, snowflake supports both structured and semi-structured data.

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Throwing Your Data Into the Ocean

Ontotext

A knowledge graph can be used as a database because it structures data that can be queried such as through a query language like SPARQL. Reuse of knowledge from third party data providers and establishing data quality principles to populate it. The connections made through these descriptions create context.

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Top Graph Use Cases and Enterprise Applications (with Real World Examples)

Ontotext

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly.