Modern data governance requires a true balancing act between enabling self-service analysis and protecting sensitive business information. Almost any organization will say they make decisions based on data, or that they want to. Scratch the surface with a few questions about the quality of that data and confidence vanishes. Move on to discuss data security and see how quickly the subject changes.
As self-service is becoming the norm in data and analytics, more business users are demanding access to data to gain their own insights and drive localized initiatives. The vast majorities of people have smart mobile devices and expect to access data from wherever they are.
“I spend less than an hour a month maintaining the environment that supports 1400 users. I have no help desk calls, the only call I get is I want another license.”
This any-device-anywhere culture will continue to grow as technology continues to become more powerful, and as data transfer rates improve globally. Let’s consider the risk of data in transit – and hatch a plan for it.
The four essential elements when building your data governance strategy:
- The team
- Data quality
- Data security and compliance
- Report and dashboard governance
Having a data implementation blueprint with executive support is imperative it also needs to bring data analytics directly to the people who understand what questions to ask with regard to the insights it can provide.
Finding a safe and effective management system for all the various data sources, including the random spreadsheets, coupled with a way to bring organizations to a higher standard of data quality, is a task that requires a combining of efforts for an IT and business approach. More precise data insights will show in terms of both increased revenues and reduced costs of operation ultimately driving better business outcomes. Organizations that understand their data can and will make better, more informed and faster decisions.
Data is clearly a key element in any business decision process today; this paper explains a few simple steps for finding confidence in data and the distribution infrastructure that makes it available.
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