Data shapes the world. It tells us all sorts of interesting things. It helps us plan, it helps us make decisions and it tells us what’s right and what’s wrong with a business. But are businesses really making the most use of their data?
There are many types of data out there. Transactional (or dynamic) data is generated or modified by the systems that are used for transactional or operational purposes, such as a cash register or an ATM. Closer to home, an IVR application or a Web page could be considered transactional systems. Customers interact with them and execute various tasks.
Examples of transactional data include what a caller said, what options they pressed, how much they owe and how they paid. Each of these events could be tied to a date, time and even a part of the world they are calling from.
Another flavor of data is analytical data. Analytical data provides the business intelligence that allows organizations to make key decisions. This type of data is often stored in enterprise data warehouses and data marts and is optimized for decision support. An example of analytical data is identifying how many people own red two-door cars in any major U.S. cities starting with the letter “M.” A more practical example is identifying the ratio of people who prefer Android to iOS and then organizing them by demographics such as sex, location or age.
The point is that data is everywhere, and if you were able to acquire the right data, it could make you competent enough to confidently run your business and help others run their businesses. This is how the buzz term “big data” got started. Let’s get some big data and all our problems will be solved, right? Wrong. It is easy to get sucked into the hype of big data or even get overwhelmed by it.
According to Wikipedia, “Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage and process the data within a tolerable elapsed time.” Most of the data out there is unstructured, epic in volume and grows at an exponential rate – all qualities that make it quite challenging and costly to manage. But if you can organize this data, then you have a leg up on the competition.
According to the big data report by the McKinsey Global Institute, “If U.S. health care were to use big data creatively and effectively to drive efficiency and quality, [then] the sector could create more than $300 billion in value every year. Two-thirds of that would be in the form of reducing U.S. health care expenditure by about 8 percent.”
The following are typical big data characteristics:
- Volume: Massive quantities of data that require extremely intense analysis and lots of hardware.
- Variety: Data is not organized, is not simple and is not just text. It could come in the form of audio, video and even imagery.
- Velocity: The data comes quick and requires fast processing.
Because of these qualities, it is becoming challenging to store the data and become savvy enough to handle it. The data comes from various sources and can be unstructured and difficult to query out of traditional relational databases and even data warehouses. There is also the security aspect of maintaining big data. With all that data being captured, it is even more important to make sure data is secure. Again, with the right plan, it is possible to reap the benefits of big data. But how do you know if your company is ready for it?
Fortunately, there are experts out there who have already gone through this exercise and provide a guideline for evaluating the feasibility of adopting big data (Forrester). And, with West’s expertise and partnerships, it is safe to say that we are a big data expert.