Flowers are static, we don’t consume them except with our eyes and perhaps our sense of smell (If they are decorative plastic flowers then there won’t even smell). In that sense they are unlike food, which we do consume and from which we derive sustenance, nutrition, and life itself. A life without flowers might be unfulfilling and perhaps even miserable, but life without food would be certain death. Same goes about Data for any Organization
And so it goes with data. Data is not static, sitting on a shelf. We keep receiving it and consume it. Data meant to be consumed by our business applications for everyday use. Provide better experience to its customers, understand the customer behavior, Identify fraud/risks, Provider deeper understanding for better business decision making.
And so it goes with data. Data is not static, sitting on a shelf. We keep receiving it and consume it. Data meant to be consumed by our business applications for everyday use. Provide better experience to its customers, understand the customer behavior, Identify fraud/risks, Provider deeper understanding for better business decision making.
Just as we need food from basic four food groups for sustainable health, data needs to Managed and Governed with following norms to make it fit for consumption
1. Data need to be Complete: Many times incomplete data leads to wrong conclusions and bad decisions.
2. Data need to be Consistent: Data does not have consistency many times it is impossible to analyze and make sense of it.
3. Data need to be Conform: Data need to conform to standards
4. Data need to be consolidated: If data is not consolidated to usable levels could lead wrong aggregations. Eliminating data duplication is very important for data management to have accurate reporting in analytic's and right information in operational side.
1. Data need to be Complete: Many times incomplete data leads to wrong conclusions and bad decisions.
2. Data need to be Consistent: Data does not have consistency many times it is impossible to analyze and make sense of it.
3. Data need to be Conform: Data need to conform to standards
4. Data need to be consolidated: If data is not consolidated to usable levels could lead wrong aggregations. Eliminating data duplication is very important for data management to have accurate reporting in analytic's and right information in operational side.
When data follow all these norms is healthy and delicious for consumption. It builds trust of business to use the data which leads to healthy decisions for the organization. When data managed consistently will keep getting better, healthier and more dependable.
The way we take care our food for cleanliness, nutritious values, calories, taste the same constant focus need to be given to data management to keep following the norms. As we getting new data sources or building new data centric applications making sure they follow same norms is equally important.
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