When it comes to making sense of data, companies have been conducting this process since the inception of computers in our society. At the time when these devices were made available in late 1980s at a cheaper price rate, companies started the utilization of BI (Business Intelligence) software to find the meaning of the data. However today, the world has paved way for much stronger and advanced big data analytics that go beyond the capabilities of Business Intelligence. Rather than taking a look back the data to understand what has happened, big data analytics assists users in using the data to look into the future and anticipate the outcome. In this journey, we’ll take you through a fascinating journey of big data analytics and how its different forms are helping to bring an element of ease in our business processes:
What is Big Data Analytics?
Big data analytics is the process of collecting, organizing and analysing large sets of data (called big data) to discover patterns and other useful information. Big data analytics can help organizations to better understand the information contained within the data and will also help identify the data that is most important to the business and future business decisions. Analysts working with big data basically want the knowledge that comes from analysing the data. (Source: Webopedia)
Generally, there are three types of Big Data analytics:
Utilising the statistical models and other methods, organizations can predict events based on the occurrences of the past. The methodologies used include data mining, statistics, machine learning and much more. Some organizations have even gone up to the extent of using predictive analytics in the entire process of sales, lead source analysis, number of communications, their types, documents, social media accounts, data of CRM etc. Moreover, predictive analytics can also be used to support marketing and other types of sophisticated forecasts.
Just like Business Intelligence, descriptive analytics makes use of past event. One of the least complicated methods, it utilizes simple calculations, aggregations of metrics and so forth. Furthermore, descriptive analytics take data mining is use for finding interrelationship between variables and assists in the identification of the reasons for previous failure or success.
According to SAS, Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.
Gradually, Big Data analytics solutions have started to be integrated with booming technologies like Internet of Things to enable the related devices to make automatic decisions in an effective and precise manner. To conclude, what we are witnessing today is just the beginning of the phenomenon that is about to change the course of entire way we approach the term “data-driven”.
If you are one of those businesses looking for big data analytics solutions, you can get in touch with a web application development company that can provide relevant solutions for all your requirements.