Dataversity

NOVEMBER 16, 2022

The news these days is full of massive fines levied against companies that failed to protect their customer data. An effective data classification approach is one of the best ways to ensure that companies can identify and protect their most valuable data. Our experience continues to […].

Data Classification 52

Data Classification Data Governance Data Quality 52

IBM Data Science in Practice

APRIL 26, 2024

Metadata Enrichment: Empowering Data Governance Data Quality Tab from Metadata Enrichment Metadata enrichment is a crucial aspect of data governance, enabling organizations to enhance the quality and context of their data assets. More on metadata enrichment can be read here.

SQL 130

SQL Data Quality Data Governance Data Scientist 130

The Data Administration Newsletter

SEPTEMBER 19, 2023

Through advanced technologies and tools, IT ensures that data is securely stored, backed up, and accessible to authorized personnel. IT also enforces data governance policies and procedures, such as data classification and access […]

Data Governance 81

Data Governance Data Classification Data Quality 81

Precisely

SEPTEMBER 5, 2023

An MDM consolidates important domain data into unique or linked instances (e.g. a “golden” record) and then uses that unique record as a reference point for aggregating associated data, purging duplicates, standardizing data across various applications, and creating rules to continuously resolve, merge, or disassociate records.

Data Governance 52

Data Governance Data Quality Cloud Computing Data Classification 52

Dataconomy

MARCH 29, 2023

It involves the creation of rules for collecting, storing, processing, and sharing data to ensure its accuracy, completeness, consistency, and security. Some key concepts related to data governance include: Data quality:  Ensuring that data is accurate, complete, and consistent.

Data Governance 70

Data Governance Data Analyst Data Quality Data Silos 70

Dataconomy

MARCH 29, 2023

It involves the creation of rules for collecting, storing, processing, and sharing data to ensure its accuracy, completeness, consistency, and security. Some key concepts related to data governance include: Data quality:  Ensuring that data is accurate, complete, and consistent.

Data Governance 70

Data Governance Data Analyst Data Quality Data Silos 70

Alation

JUNE 14, 2021

Do we know the business outcomes tied to data risk management? These questions drive classification. Once you have data classification then you can talk about whether you need to tokenize and why, or anonymize and why, or encrypt and why, etc.” Data Collaboration Data discovery has increasingly become a team sport.

Data Governance 97

Data Governance Data Lakes Data Classification Data Quality 97