Today we continue discussing the best practice from storage engineering:
- 375) Most storage products don’t differentiate between human and machine data because it involves upper layers of data management. However, dedicated differentiation between human and machine data can make the products more customized for these purposes.
- 376) Data storage requirements change from industry to industry. Finance data storage is largely in the form of distributed indexes and continuous data transfers. A cold storage product does not serve its needs even if the objects are accessible over the web
- 377) Finance data is subject to a lot of calculations and proprietary and often well-guarded calculators that have largely relied on relational databases. Yet these same companies have also adopted NoSQL storage in favor of their warehouses. As their portfolios grow, they incubate new and emerging features and increasingly favor new technologies
- 378) Finance data is also heavily regulated. The Sarbanes-Oxley act sought to bring control to the corporations in order to avoid accounting scandals. It specified disclosure controls, audit and the compliance terms
- 379) Health industry data is another example with its own needs around data compliance. The Health insurance portability and Accountability act required a lot of controls around who, when and where can get access to personally identifiable information
- 380) Health data is often tightly integrated into proprietary stacks and organizations. Yet they are also required to participate in providing web access to all the information surrounding an individual at the same place. This makes them require a virtualized cross company data storage.
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