If you are newly ventured into the world of technology, you may find yourself grappling with new terms that seem hard to understand. Take for instance Big Data. What exactly is it? Big data is a catchphrase that is used to describe structured and unstructured data that is so massive in volume that it cannot be analyzed using the traditional processing techniques. That’s where database management solutions companies like Altibase, Oracle, Microsoft, IBM and others come into play. As far as big data is concerned, there are three mains Vs that are used in its definition. These are volume, velocity and variety.
Over the years, data has become increasingly available, leading to increased volume. The onset of online transactions meant that there was more data getting acquired from these transactions, and the same goes for social media where data is being gathered on a daily, nay, minutely basis. Sensor and machine-to-machine data gathering has also increased and this has led to an increased volume of data, especially considering that it is now cheaper to store data than it was in the distant past.
The velocity at which new data is coming in is unprecedented. Sensors, smart metering and other applications have made it possible to relay large amounts of data in real-time. Such that not only do enterprises and organizations have to deal with large volumes of data, they must do so in timely fashion as the data is incoming at a very high speed.
The data that is available in today’s world comes in many different formats. There is structured, numeric data in traditional databases and unstructured data in text documents, emails, videos and so on. This variety of data contributes to big data, and organizations have to find ways to manage, merge and govern these varieties if they are to be useful to the said organization.
Even though the term big data does refer to the volume of the data at hand, it is usually used to describe the technology used to handle the processing of such data. In fact, in practical usage, the term big data is rarely used to refer to the actual size of a data set.
Big data is important to businesses because more data leads to more accurate analyses. If companies have more accurate analyses, it means they can carry out their decision-making more confidently. Ultimately, better decisions will lead to improved efficiency, cost reduction and lowered risk.
One very important fact that businesses need to remember is that when it comes to big data, the real issue is not how much data you are able to gather. Rather, it is about what you do with the data. “We use big data to analyze sales trends and says Ihab Barrawi, President and CEO of Buy Railings, one of the world’s largest retailers and manufacturers of decorative reailings. As such, it is important to pair the data collected with high-powered analytics which will produce relevant data and analyses that can be used to positively impact the business.