Databases Reference
In-Depth Information
Collaboration
Collaboration is the new trend in the big data scenario, whereby data assets are
commoditized, shared, and offered as a product of data services. Data democratization is
a leading motivator for this trend. Large data sets from academia, government, and even
space research are now available for the public to view, consume, and utilize in creative
ways. Data.gov is an example of a public service initiative where public data is shared and
has sparked similar initiatives across the globe. Big data use cases are reported in climate
modeling, political campaign strategy, poll predictions, environment management,
genetic engineering, space science, and other areas.
Data aggregators, data exchanges and data markets such as those from InfoChimps,
Factual, Microsoft Azure market place, Axciom and others have come up with data service
offerings whereby “trusted” data sets are made available for free or on a subscription basis.
This is an example where data sets are assessed with an inherent value as data products.
Crowdsourcing is a rapidly growing trend where skilled and passionate people
collaborate to develop innovative approaches to develop insights and recommendation
schemes. Kaggle offers a big data platform for predictive modeling and analytic
competitions effectively making “data science a sport.” Visual.ly offers one of the largest
data visualization showcases in the world, effectively exemplifying the collective talent
and creativity of a large user base.
The possibilities for new ideas and offerings will be forthcoming at a tremendous
rate in the coming years. As big data technologies mature and become easier to deploy
and use, expect to see more solutions coming out especially merging with the other areas
of cloud, mobile, and social media.
There is widespread awareness of the revenue and growth potential from enterprise
data assets. Data management is no longer seen as a cost center. Enterprise information
management is now perceived to be a critical initiative that can potentially impact the
bottom line. Data-driven companies can offer services like data democratization and data
monetization to launch new business models.
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Data democratization, the sharing of data and making data available to anyone
that was once available only to a select few, is leading to creative usage of data such as
data mashups and enhanced data visualization. Data monetization (i.e., the business model
of offering data sets as a shareable commodity) has resulted in data service providers such
as data aggregators and data exchanges.
Note
Big data analytics can thus enable new business opportunities from an operational
perspective. They provide effective utilization of data assets and rapid data insights into
business processes and enterprise applications and also enhanced analytical capabilities to
derive deeper meaningful insights in a rapid fashion, action on business strategies through
these enhanced insights into the business and exploitation of missed opportunities in areas
previously overlooked. These opportunities arise from the key premise in big data: all data
has potential value if it can be collected, analyzed, and used to generate actionable insight
and enhance operational business capabilities.
