Discovery and Data Governance Go Together Like Unicorns and Rainbows

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Imagine your organization running so smoothly that all decisions are based on trusted data. Sounds pretty good, huh?  We want to help organizations like yours drive decision integrity – by empowering you with the ability to discover the right data and make the right decisions faster.

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Announcing the Information Value Management® Integration Capabilities for SAP

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We are proud to announce the availability of new integration capabilities that allow Information Value Management® (IVM) to interoperate with SAP Information Steward Software. The processes in IVM® for defining data strategy and policy can now work together with the data management functions in SAP Information Steward and other SAP solutions for enterprise information management (EIM) that provide data quality, master data management, content management, and information lifecycle management, supporting a comprehensive solution for information governance.  

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A New Approach to Metadata Management Through the Eyes of the Business

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Since the popularity of our Information Value Management® solution has grown so has the question “how does this compare to or compliment metadata management?” There are distinct differences between the two based on the unique challenges we have observed and tackled in the collective 300+ man-years of data governance experience we have within DATUM LLC. The purpose of this blog is not to question the value of metadata management. There is a very real need to discover and document attributes that describe the context of data, but the needs for the IT organization are distinctly different from the needs of the Business in that regard. This gives rise to a different approach through Information Value Management® (IVM). Before we can discuss a new approach, we must understand the current position of metadata in an organization.

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Any Successful SAP HANA Initiative Better Have SAP MDG Along for the Ride

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Business Intelligence (BI) has been, and is going to be a big differentiator for companies for years to come. Historically, Business Intelligence practitioners knew what questions they wanted to ask and that the answers were available; but the problem was that by the time they figured out how to execute against those answers, the opportunity had passed by. With SAP HANA as the foundation for the transactional ECC system as well as the BI layer, that restriction does not exist anymore. The immense amount of data that a system like SAP HANA can store, analyze and report from removes almost any technical limitation BI analysts had in the past. Therefore, the companies that can ask the right questions, make the correct decision and execute efficiently against the strategy will be the ones that win.

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Data Governance: When Excel Doesn’t Cut it Anymore

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To anyone in the trenches associated with Data Governance and Enterprise Data Management, one thing is certain: it is a daunting task. Data should be put high on a pedestal – after all, it’s the core foundation that all business processes, applications and reporting tools execute against!

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Best Practices for Implementing SAP Master Data Governance

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Bad Master Data. If you are involved with Master Data, then you know how bad it can get. You know that it affects everything in the enterprise. As master data starts impacting the bottom-line, the CIO will have to preside over wrangling in some formal data governance - whether it be a tool like SAP MDG or any another enterprise governance solution. Most of the time, it's a shotgun wedding announcement in a company memo: Neglectful Data Organization Marries Standardized System of Record.

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Types of Data to Consider for a Migration

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Data is a generic term that is used to describe all of the information that is required to drive the operational processes for the business.

Many migration programs have the myopic perspective that ALL data is required, when this simply is not the case. Trying to migrate every piece of information can actually hinder growth and performance after your "Go Live" by clogging the system with unnecessary data.

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