Data has become the vital part of any business activity these days. Companies need to deal with massive amounts of data and transform it into useful information that can help them achieve their objectives. The transformation can be in the form of reports, dashboards, maps, visualizations, etc. and is known as big data concepts. However, the term ‘big data’ refers only to the magnitude of the data and not its quality. Let us see how the quality of information can be improved over the existing big data concepts.
First of all, big data refers to the velocity of data. In order to understand this concept, we need to understand what are the different types of velocity. One of them is unstructured data sets, which include unprocessed text, unprocessed images, raw audio and video files and so on. The other type of velocity is structured data sets, which include processed text, processed images, high-quality audio and video, etc. Thus, both the types have their own advantages and disadvantages.
Unstructured data sets can store huge volumes of information, but this comes with two major problems. One is the time involved for maintaining the data. Another is its huge cost, which makes it impractical for organizations to adopt it as a main data processing platform. On the other hand, structured data processing involves massive volumes of processed data but the source is always reliable and available.
What is more, the notion of big data refers not only to increasing volumes of data, but also to improving the quality of such volumes. This quality factor imparts enormous leverage to companies, especially in operational activities. For example, if a traditional database contains records that are highly inaccurate and outdated, it will take a lot of time for database operations. Even if the company invests in a good data cleansing tool, it won’t be able to get rid of outdated information for which it needs a new set of indexes. However, a well-maintained, robust, traditional database can easily overcome such obstacles by using precise tools for data transformations. Again, time becomes a critical constraint.
Now, what is important here is to understand how big data collection, along with advanced analytics, can help companies achieve their objectives. The social media aspect of things is something that many companies have ignored till now. While traditional databases may contain information about customer demographics and purchasing habits, social media allows businesses to access the latent customer information stored deep inside the psyche of an individual.
This information can help companies fine tune their marketing campaigns. It can help them better target their customers. It can also help them increase brand awareness. Using sophisticated tools for analytics, companies can use big data for their purpose and that too in a manner that fully complies with the principles of structured data. So here we have a double edge sword.
Companies who are already using this unstructured data technology can take advantage of its value and benefit immensely. But on the other hand, those who haven’t are losing out on a lot of opportunities. By adopting a process using traditional analytical methods, they are in fact missing out on an untapped resource, which is what big data concepts represent.
So we see that the big data concept refers not to unstructured data sets, but to structured, managed data sets. And as long as businesses make use of such techniques, they will reap maximum benefits. It all starts with understanding what it is and what it can do. Then only one can rightfully say that this is a revolution that is sweeping across various industries-and has the potential to do great things for the corporate sector.