Big data is a term that we hear more and more nowadays. The need that many businesses have for handling big data has even created a whole industry in terms of cloud storage and cloud computing solutions for example. The reason why big data is so important to companies of all kinds is actually very simple – having more data usually means more accurate analyses. More accurate analyses in turn offer a better way to make the right decisions.
But what exactly are the factors that define what big data is? It can be defined using the three Vs – variety, velocity and volume.
- Variety – big data nowadays is available in all shapes and formats. One of the most popular types is numeric structured data which can be found in traditional databases. Other types include financial transactions, stock ticker data, audio, video, email and text documents. Many businesses and organizations have difficulties governing, merging and managing the different types of data that they have.
- Velocity –another challenge that many organizations face when handling big data is the incredible speed that it is streaming in at. Working with data from smart metering, sensors and RFID tags for example require businesses to be able to manage it almost in real time. Being able to react quickly and deal with it all can be very overwhelming.
- Volume – big data is, of course, characterized with its large volume. This can be anything from unstructured data coming in from social media to years of transaction based data. In the past, organizations had to figure out a way to store the huge amounts of data they had. Nowadays, however, the prices for cloud storage and other solutions have dropped significantly. Despite that fact, businesses still have to figure out a way to quickly determine whether the data they have is relevant and how to get the most out of it using analytics.
According to some people, big data can be defined by two more factors:
- Complexity – nowadays, data is streaming in from all kinds of different sources, which presents another challenge that organizations have to figure out how to deal with. Being able to transform, cleanse, match and link data across different systems is very important when you don’t want it to quickly spiral out of your control.
- Variability – variety, velocity and volume are not the only Vs you might have to worry about. Sometimes big data flows come and go unexpectedly. Some organizations experience peaks that are results of seasonal events or social media trends for example. And when unstructured data is involved, things get even messier.
Organizations usually have the same goals and ideas for the big data they store. They all want to use the data they have and analyze it to find solutions that enable making smarter business decisions, optimized offers and development of new products, time reduction and cost reduction.
Big data can definitely make a big difference for any organization if it is properly handled. UPS is a great example of a company that manages huge amounts of data to save millions of gallons of fuel per year by reducing the miles that its drivers travel annually. You can find out how to leverage cloud computing to help with Big Data analysis in the video by Mark Hurd of Oracle:
The real problem for businesses is not getting and storing huge amounts of data – it’s what they do with it and how they use it to make it mean something. Every year we store more and more data in comparison to previous years and it is estimated that by 2020 the total amount of data stored will be 50 times larger than what we store nowadays.