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Every day, every hour, every minute we generate data based on our smartphone use, computer use, Internet application use and more. From going to the doctor’s office to checking out at the grocery store, data is generated that can help businesses and healthcare deliver services more effectively and help the consumer custom care. The massive amount of data being collected requires powerful tools to navigate and apply effectively.
Big Data Requires Powerful Computing Tools
In their Big Data Analytics report, CIO Magazine suggests the corporations must be prepared to make a strategic investment in BIg Data. First, companies must invest in infrastructure that can “support the constraint of Big Data analytics.” [1] This includes but is not limited to an architecture that incorporates data warehouses, private cloud, in-database analytics, analytic appliances, high-performance computing, and complex event processing.
A business needs the power for rapid processing of detailed structured and unstructured data. This processing power allows businesses to solve complex scenario queries in a timely manner. As a result, many large companies may implement an in-database analytics solution that bascially brings the analytics to the data environment, allowing them to “manage, provision and govern data, and get faster insights.”
Additionally, businesses must develop/implement discovery/exploration toolsets that make the process of generating reports flexible, fast and duplicatable across the organization. This involves applications support as well as trained personell. The size of allocated resources for an effective Big Data solution seem well out of reach for SMBs.
How can a company with limited resources utilize the power of Big Data?
[1] Big Data Analytics. CIO, June 2012
[2] Brian Hopkins and Boris Evelson. “Forrester: Big data – start small, but scale quickly.” Computer Weekly < http://www.computerweekly.com/opinion/Forrester-Big-Data-Start-Small-But-Scale-Quickly>
2013-01-25 17:07:48
Source: http://blog.integracon.com/2013/01/25/leveraging-the-power-of-big-data-in-the-smb/