Data management is nothing if not a broad discipline. And many IT managers and other technology professionals don’t...
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enjoy the luxury of being specialists within that discipline. They have to get involved with data across the data management spectrum, from capture, cleansing and integration on up through data governance and management of databases and data warehouses.
With that reality in mind, we offered up tips and advice on a variety of aspects of the data management process over the past month, starting with a look at data governance best practices through the eyes of data management pros at Nationwide Mutual Insurance and pharmaceutical and medical services provider Cardinal Health. Their message to others launching or planning governance programs: Be prepared for setbacks and use a combination of top-down and bottom-up implementation approaches.
Next up was a case study about a data integration project at Ultimate Medical Academy (UMA), which offers training classes for nursing assistants, radiology technicians and other medical professionals. UMA had to integrate a new hosted learning management system running on an Oracle database with its student information system and other on-premises applications that are built on SQL Server -- and it managed to put the required links in place within a month by keeping the project scope narrow and not being shy about calling in vendor help when needed.
For many organizations weighing their data warehouse strategies and plans, data warehouse appliances have become a viable alternative to traditional warehousing systems. But analysts and IT managers note that in building a business case for an appliance purchase, the burden of proof typically will be on you showing that the hardware and software bundles would provide advantages over the conventional options. Don’t just get enamored with appliances, cautioned Enterprise Strategy Group analyst Julie Lockner: “You don’t want to invest in technology that won’t work tomorrow,” she said.
Some people might view master data management (MDM) as the forgotten piece of the data management puzzle. But if MDM remains a mystery to many on the business side of organizations, it can hold the key to data consistency and accuracy throughout a company. Gartner Inc. held its annual MDM Summit this month, with topics ranging from moving up the MDM maturity ladder to predictions of how “big data” will affect MDM programs. In the midst of all the Gartner talk, an exec from Intel Corp. boiled the semiconductor maker’s MDM strategy down into these four words: standardize, consolidate, optimize and utilize.
Come to think of it, that’s not a bad mantra for the entire data management process.
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