What is Big Data?
“Big data” is a term used to describe the availability of data and its exponential growth. What is more, big data may be as important as the Internet is to business and society as we know it. Why, you might ask? More data can lead to more a more accurate analysis. A more accurate analysis can lead to more confidence in decision-making, and confident decisions can yield greater efficiency in cost reductions and risk reductions.
Back in 2001, industry analyst, Doug Laney, discussed the now mainstream meaning of big data as the “three Vs”: volume, velocity, and variety.
An array of variables contribute to the expansion of data volume, such as transaction-based data stored over the years, unstructured data that streams in social media, and expanding machine-to-machine and sensor data that is gathered.
In the past, too much data volume created a storage problem. However, with a reduction in storage costs, other issues began to arise, like how to gauge relevance within large volumes of data and how to employ analytics to develop value from relevant data.
Data streams at an unprecedented rate, which is why it has to be contended with in a responsive manner. Sensors, RFID tags and smart metering fuel the need to respond to torrents of data immediately. Reacting fast enough to handle the data velocity is a continual challenge for most companies.
These days, data comes in a variety of formats, from structured and numeric data in traditional databases, to information rendered from business applications (depending on the type of service).
Additional Dimensions to Think About
There are also two helpful dimensions to consider when thinking about big data. In addition to the increasing varieties and velocities of data, data flow can be highly sporadic with random peaks. It may indicate something trending in social media. Variables such as daily, seasonal, and event triggers that instigate peak data loads can be difficult to gauge and manage—compound that with unstructured data, and you have an even greater challenge on your hands.
Today’s data generally comes from many sources, and it is still quite an endeavor to link, match, cleanse, and convert data throughout systems. It is necessary, however, to connect and compare the relationships, chain-of-commands, and multifold data links to prevent your data from very quickly spiraling out of control.
Why Big Data Matters to You
The real issue is not that you are procuring large volumes of data. Rather, what you do with the data is what truly makes an impact. Organizations should have the knowledge to gather data from any source, channel relevant data, and evaluate it to find answers that enable reductions in costs, reductions with time, new product creations and optimized offerings, and smarter decision-making.
Retail and consumer product companies study social media platforms like Facebook, Pinterest and Amazon to gauge customer behavior, taste, and product or service perception. Manufacturers observe minute vibration data from their machinery, which can slightly change as it wears down. This helps the determine the best possible time to maintain or replace equipment. Replacing it too late instigates costly work stoppage, and replacing it too soon is a waste of money.
Manufacturers also monitor social networks, but not for the same pursuits as marketers. They utilize social media to discern aftermarket support problems before a warranty malfunction becomes a public detriment.
Moreover, Insurance companies apply Big Data to gauge which home insurance applications can be processed immediately, and which others need to be validated by a visit from an agent in person.