SAS Data Management
@SASDataMGMT
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News, trends and insights on SAS #datamanagement tech | #dataquality | #dataintegration | #datagovernance | #MDM | #BigData | #dataprep & more
Cary, NC
Joined March 2009
3 ways to prepare data for analytics: How to choose the best option.#datamanagement.
blogs.sas.com
Jeff Stander evaluates the pros and cons of three different options you can use to prepare your organization's data for analytics.
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Top 5 ways business glossaries make analytics better.#datamanagement.
blogs.sas.com
From improving data quality to operationalizing analytics, Jim Harris explains why business glossaries make analytics better.
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Why data management protocols are key to implementing legislative actions.#datamanagement.
blogs.sas.com
David Loshin explains the significant role the data team plays in enforcing certain legislative actions, citing the "double-dipping" act as an example.
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The convergence of data and model governance.#datamanagement.
blogs.sas.com
Jim Harris proposes that data governance policies for analytics could serve as the foundation for a formal model governance program.
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Reflections on the data-related challenges of today and tomorrow.#datamanagement.
blogs.sas.com
Some things change – others surface repeatedly. Phil Simon reflects on a variety of data-related challenges, current and future.
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Digital transformation revises the role of the CIO.#datamanagement.
blogs.sas.com
David Loshin offers four suggestions for CIOs who are looking to shape successful digital transformation initiatives.
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The case against automating data management.#datamanagement.
blogs.sas.com
Phil Simon argues against full automation of data management – opposite the viewpoint shared in his previous post.
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How data can change your business – if you let it.#datamanagement.
blogs.sas.com
Jim Harris says it's not enough to be data-driven – understand which data is driving your business, and whether it's leading you to make better decisions.
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The case for automating data management.#datamanagement.
blogs.sas.com
New tools and automation are essential for managing today's data. Phil Simon looks at the pros of automating data management in Part 1 of this series.
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3 tips for building a better data lake.#datamanagement.
blogs.sas.com
In Part 2 of his series, guest blogger Khari Villela explores the common pitfalls of building a data lake and shares tips to help you skip those mistakes.
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Reference data and data governance.#datamanagement.
blogs.sas.com
Based on three recent developments, David Loshin suggests that reference data could be the foundation of future governance structures.
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How data quality improves artificial intelligence – Part 2.#datamanagement.
blogs.sas.com
Jim Harris shares three more examples of how data quality improves artificial intelligence in Part 2 of his series.
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Data governance implications of increased data privacy regulations: Information risk.#datamanagement.
blogs.sas.com
Data protection applies to different individuals in different contexts. David Loshin reminds us that we're not limited to complying with GDPR and CCPA.
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Which data sources will organizations use to make AI as effective as possible?.#datamanagement.
blogs.sas.com
Data makes artificial intelligence better and smarter. Phil Simon weighs in on using data to make the most of AI.
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How data quality improves artificial intelligence.#datamanagement.
blogs.sas.com
All AI applications are data-driven and dependent on high-quality data. Jim Harris shares examples of how data quality improves artificial intelligence.
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