More than 2.5 quintillion bytes of data are generated every day. The data is received from sensors used to accumulate climate information, digital pictures, posts on social networking websites, transaction records, GPS etc. This is big data. There are three basic types of data:
- Machine generated or sensor related data: This would include all Call Detail Records, smart meters, equipment logs, trading systems data, web logs etc.
- Traditional business enterprise data: From customer information generated in the CRM to transactional ERP, this contains web store transactions and general ledger data.
- Social networking data: This includes micro-blogging data from micro-blogging websites, social networking like Facebook and customer feedback streams.
The McKinsey Global Institute predicts data volume to grow by 40% per year. Though the volume is the visible stricture, other characteristics also define Big Data.
- Volume: Nontraditional data is less than the machine-generated data. Example, 10TB of data is created in 30 minutes by a single jet engine. With thousands of flights, the daily volume of this data runs in Petabytes. Oil refineries and drilling rigs generate same volumes of data concocting to the problem.
- Velocity: Not as massive as the machine-generated data, social media streams produces an influx of assessments, relationship etc that is valuable for CRM. 140 characters of tweet can generate high velocity 8TB data per day.
- Variety: The nontraditional data formats change randomly. As the new services are being deployed, new data structures need to capture resultant information. On the other hand, traditional data formats evolve slowly and is usually well defined.
- Value: Each data have their specific economic value. Relevant information often lay hidden in non-traditional data. It is important to identify the valuable data, transform and extract it for analysis.
To exploit the potential of big data, it is important to evolve accordingly. The infrastructure should be able to handle rapid data delivery, its varying types etc that can then be transgressed to the organization for analysis.
Benefits of Big Data:
David McQueeney, IBM’s Head of Software Research, said that most organizations are sitting on huge repositories of data that can be used to run the business better. Big Data can be distilled, analyzed, integrated with traditional enterprise data to provide an insight into the business. This leads to enhanced productivity, innovation and provides a competitive edge to the business, impacting the bottom line.
It is now time to exploit Big Data. McQueeney continued to say that whatever the type of enterprise (private, non-profit or government) there is a mountain of data. Unstructured data contains prospective insights that can be converted and used to impress/ engage customers and run the process more seamlessly.
Computing would analyze data and use insights that can be refined, streamlined and converted to something powerful. The results found were influential, enabling to view the same information from five or six different views that would facilitate in predicting the future.
For example, in healthcare industry, management of chronic conditions becomes expensive. The home monitoring devices can assess vital signs to supervise the health and thereby reduce extra overhead costs and visits.
Manufacturing industry can deploy sensors that return stream of telemetry, which is used to deliver services. The telemetry also denotes the user patterns, opportunities and failures to improve productivity and decrease the assembly costs.
GPS devices and Smartphones facilitates in advertising an opportunity that targets consumers close to the store. New revenue channels are opened and businesses targets wider audience.
The retail sector uses the data to moderate the customers who decided against buying and make the information available for the implementation of a better plan. There is a marked improvement in productivity. Social media exists for Big Data. To fabricate an enhanced user experience, the business model of most social networking websites captures the relevant data about the member.
Evaluation of data to increase growth of an enterprise:
Evaluation of newer streams of data reveals sources and opportunities of economic value that would provide a fresh perspective to identify the market matrix. It is important to be comprised of appropriate tools to acquire, organize and capture of all types of data to make the most informed decision.
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