Price: $31.78
(as of Dec 22,2024 21:53:10 UTC – Details)
ASIN : B00QPHPT1M
Publisher : Mc Press (January 1, 2015)
Publication date : January 1, 2015
Language : English
File size : 11389 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 366 pages
Page numbers source ISBN : 1583478442
Data governance tools are essential for organizations looking to effectively manage and protect their data assets. With the rise of big data and the increasing importance of data governance in ensuring compliance with regulations such as GDPR, selecting the right data governance tools is crucial.
When evaluating data governance tools, there are several key criteria to consider. These include:
1. Data Quality: One of the primary goals of data governance is to ensure data quality and integrity. Look for tools that offer features such as data profiling, data cleansing, and data lineage to help maintain the quality of your data.
2. Metadata Management: Metadata provides crucial information about your data, such as its source, format, and usage. A good data governance tool should offer robust metadata management capabilities to help you understand and track your data assets.
3. Policy Management: Data governance tools should allow you to define and enforce data policies across your organization. Look for tools that offer policy management features, such as policy creation, enforcement, and monitoring.
4. Data Security: Protecting your data from unauthorized access and breaches is essential for data governance. Choose tools that offer strong data security features, such as encryption, access control, and audit trails.
5. Scalability: As your organization’s data grows, the data governance tool you choose should be able to scale to meet your needs. Look for tools that offer scalability and flexibility to accommodate your organization’s data growth.
In addition to these criteria, it’s important to consider how data governance tools align with your enterprise data management strategy. Data governance should be integrated with other data management initiatives, such as data integration, master data management, and data quality management, to ensure a cohesive approach to managing and utilizing your data assets.
By carefully evaluating data governance tools based on these criteria and ensuring alignment with your enterprise data management strategy, you can effectively govern your data assets and derive maximum value from your data.
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