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.”  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 discovery/exploration toolsets that make the process of generating reports flexible, fast and easy to duplicate across the organization. This involves applications support as well as trained personnel. 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?
Big Data utilization requires processing power and effective tools; it is not out of reach for smaller businesses. Brian Hopkins and Boris Evelson at Forrestor Research suggest refining the definition of Big Data as “techniques and technologies that make handling data at extreme scale affordable”.  Big Data is driving new process, new technologies and analytic programs that is making the processing potential more accessible to smaller companies.
By utilizing cloud resource, open source tools such as Apache Hadoop, taking advantage of freely shared data via government or other sources, SMBs can begin forming a strategy for utilizing the insights and predictive models generated by Big Data. Forrestor has suggested one the key challenges for businesses is finding people with the appropriate analysis skills.
Gartner, Forrestor, Intuit and other research organizations, predict that Big Data will be more accesible and play a great role in the overall economy including SMBs. Now is the time for SMBs to begin listening in on the Big Data conversation, learning more about how it might speak to your specific organization, and consider a scalable solution for implementation.
 Big Data Analytics. CIO, June 2012 <http://www.cio.com/article/708604/Strategic_Guide_to_Big_Data_Analytics>
 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>