Big data ecosystem

Digital data explosion is beyond control as evident from the digital data being pumped into the digital world without relevance. The data so generated calls for special techniques, to manage and distill the essence out of it. Data follows the data lifecycle. In a larger parlance data co-exist  in a digital world and is a part of digital ecosystem. The digital ecosystem is still at its infancy. To start with digital data is brought to life through the interaction with digital gadgets by the digital users on a minute by minute basis. This is followed by aggregation of such data, analysis, and interpretation. There are other elements like the data platform, associated operating system, data storage, access mechanisms, data processing software, specialized resource, associated vendors, etc forming a part of this large ecosystem. Digital data ecosystem contributes to the genesis of bigdata ecosystem. Big data initiated by Douglass Read Cutting is an envelop term describing the management of very high volume data.  Interactions within the digital ecosystem by itself a study and calls for larger understanding of the system and their dynamics.

Looking at the volume of interactions every minute the generated digital data is beyond comprehension. In a business sense, the business community is interested to understand the digital data and exploit it for their bottom line management. This is in line with the Law of survival, looking for more cheese.  The same could be achieved through the data distillation process with or without appropriate catalyst into something newsworthy and the info-graphic chart which is used to carry the news to whomever it may concern. However digital data management is different from digital info-graphics and each of them calls for different skill sets creating a paradox.

Some of the larger questions include, the ways and means of addressing big data capture and storage management architecture, Ways and means of redefining the infrastructure architecture, modeling business intelligence to look for specifics either by heuristics, fuzzy logic, or investigative statistics, Development of info-graphics capabilities like timeline info-graphics, statistical info-graphics, process oriented info-graphics, etc, within the organization, remodeling organizational data strategy to address organizational dynamics on demand and reshaping the organization to circular designs. Big data strategy needs to also account for new sources of data, and ways of integration for timely, accurate access to information leading to business decisions.

Author- IT for Management, Oxford Press.