Big Data, the large and complex data sets collection that are difficult to manage with traditional data processing applications, is here to stay. Most organisations engage in big data to monitor analytics in real-time, understand trends, optimise pricing, identify customers, highlight promotions and do everything else that will help propel their business on the growth charts.
IBM through a use case example illustrates how retailers are getting big data savvy to define their business strategies. However, despite this strong co-relation with analytics it would be wrong to use big data interchangeably with another important trend in the global business landscape – Business Analytics.
Big Data vs Business Analytics – Variations in Form
Big Data varies vastly in form from the normal analytics. SAS, the leading name in Analytics software, in its explanation of Big Data identifies three principal attributes that characterises its nature and form. These are:
- Volume – As Organizations use sources like social media, business transaction, sensors, machine-to-machine data that are capable of generating unlimited volumes of Data.
- Velocity – Such huge volumes of Data are streaming at unprecedented speeds and needs to be captured through technology innovations like RFID tags, sensors and smart metering.
- Variety – Data is captured in both structured and unstructured formats thereby ensuring the huge variety made available.
Business Analytics, in comparison, is largely one-dimensional. It is driven primarily by its core metrics that is financial analytics. Organizations may use Big Data to also perform business analytics but does not limit the utility of this huge data mass to only monitor and measure the business metrics.
Big Data Vs Business Analytics – Machine Vs Human Intervention
The volume and variety of data made available through Big Data makes it impossible to be managed and monitored by humans alone. It has made it possible for humans to move out of the machine and let it do its own work effectively. It might require human monitoring but is definitely not dependant on human control to continue its processing.
Business Analytics on the other hand is essentially human driven. No matter how big or varied the data made available, there will be a team of analysers who would be employed to browse through charts, spreadsheets or numbers to make a business decision. As Cathy O’Neil of Mathbabe.org very rightly mentions “no matter how big the data you use is, at the end of the day, if you’re doing business analytics, you have a person looking at spreadsheets or charts or numbers, making a decision after possibly a discussion with 150 other people, and then tweaking something about the way the business is run.”
“If you’re really doing big data, then those 150 people probably get laid off, or even more likely are never hired in the first place, and the computer is programmed to update itself via an optimization method.”
Big Data does not only provide answers. It helps executives to ask the right questions. As Cathy O’Neil opines in Mathbabe.org, big data also in a banking is a microscopic and detail oriented approach to collecting every facet of information available to help organizations take critical decisions and hence the future of big data is very fast. Business Analytics on the other hand helps in tracking a single aspect of an organization’s business decisions and has a more uni-dimensional approach. Therefore, while one (Big Data) is the whole, the other (Business Analytics) can be seen as a part of the whole.
Confused as to whether your organisation needs Big Data or Business Analytics or both? Get in touch with our expert consultants today!
Author: Kishore Kapoor
Kishore Kapoor an industry veteran of 31 years in global banking technology. A Founder & CEO of eKutumb.com – World’s first marketplace for enterprise software delivery and consulting business by creating value for all of industry stakeholders involved (customers, partners, individuals and investors) through a disruptive and trans-formative approach of doing business.