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Anne Buff

Anne Buff is a business solutions manager for SAS Best Practices, a thought leadership organization at SAS Institute. She specializes in the topics of data governance, MDM, data integration, and data monetization.

Articles by Anne Buff

Emerging technologies are outpacing data governance at a rapid clip. Specifically, the rate of growth and development of emerging technologies in areas such as artificial intelligence (AI), the Internet of Things (IoT), and machine learning (ML) drastically exceeds the current speed and willingness of businesses to change their governance models to manage and protect their data and information assets. Unfortunately, the larger the delta becomes between the advancements in technology and the changes in governance, the greater the risks and losses for the business.

Posted January 09, 2018

Businesses of all sizes across all industries are rapidly adopting digital transformation models that put data at the center of driving the business forward—as they should. However, putting data at the center of everything the business does can be risky without proper planning and rigorous management. Many companies have been wise to introduce data governance programs to protect corporate data assets and establish a framework for operational excellence when it comes to data management and use. Data governance emphasizes the enforcement of defined standards or policies and provides mechanisms for consistency and repeatable processes, but it is not enough to protect businesses in today's world of data.

Posted September 20, 2017

You will often hear experienced practitioners and consultants suggest that there is both an art and a science to effective data governance. The art is in the details of fine-tuning a data governance program to fit your culture and address specific business needs. But the fundamental principles of data governance are best understood and executed through science.

Posted May 15, 2017

Governing and managing big data are not easy tasks. In fact, let's be honest—data management and governance for data of any size is no walk in the park. But, big data makes it even tougher. From integrating the disparate data sources of seemingly unending variety to curating the chaos in the heaps of unstructured data, managing the craziness we lovingly refer to as big data is not for the faint of heart. Even for those tough as nails, the challenges of big data management can be more than frustrating. So, now that you know you are not alone in dealing with this insanity, here are a few ways to make the frustrations of big data a little less intense.

Posted April 07, 2017

The focus of data governance should not be on creating bureaucracy and rules, but instead on business enablement within context of use. To do this, I suggest looking at data governance not as enforcement of a discipline, but instead as a process of guiding a data expedition. Let's look at what a data expedition entails and how data governance will be the guide of this ongoing journey.

Posted October 13, 2016

When working with data governance practitioners, I often hear comments that indicate pockets of data governance excellence (the proverbial half-full glass) or silos of data governance (half-empty) as they work toward the common goal of enterprise data governance. This is often accompanied by an observation that "if we could just get everyone to follow the rules (the same rules), then we could truly and successfully govern at the enterprise level."

Posted June 09, 2016

One of the most common challenges organizations face when developing an enterprise data governance program is the presence of data silos or pockets of data initiatives scattered throughout the company with little to no association or collaboration of efforts. While many describe their data systems as "siloed," the disjunction is less about the underlying technology and far more about the division created between lines of business.

Posted March 25, 2016

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