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What is Data Classification? Guidelines, Types, & Examples

Alation

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Manual Data Classification.

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Why Your Master Data Management Needs Data Governance

Precisely

Master Data Management systems (MDM) play an important role in harmonizing data assets across large and midsize enterprises. However, to get optimal value from your organization’s data, you need to apply the discipline of data governance to your MDM. How can they contribute their expertise?

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Building a Data Culture with Snowflake: A Guide for CIOs

phData

Data as the foundation of what the business does is great – but how do you support that? What technology or platform can meet the needs of the business, from basic report creation to complex document analysis to machine learning workflows? The Snowflake AI Data Cloud is the platform that will support that and much more!

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Data protection strategy: Key components and best practices

IBM Journey to AI blog

Data protection policies and procedures Data protection policies help organizations outline their approach to data security and data privacy. Additionally, some data protection laws and regulations require them.

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Alation 2022.1: Customize Your Data Catalog

Alation

“Time is money,” said Leonard Kwok, Senior Data Analyst, ARC. “The quicker we can fix data, the sooner we can deliver to customers on time. Manual lineage gives us a quick and easy way to document data relationships and trace where it came from. Data classification via tags is a simple yet powerful capability.

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How to Migrate from dbt Core to dbt Cloud: phData’s Simplified Approach

phData

The benefit of having a smaller number of larger projects is you’ll unlock a complete view of model lineage and have richer documentation across functional areas. These projects should include all functional areas within the data platform including analytics engineering, machine learning , and data science.

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Multiple data applications and formats make it harder for organizations to access, govern, manage and use all their data for AI effectively. Scaling data and AI with technology, people and processes Enabling data as a differentiator for AI requires a balance of technology, people and processes.

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