Big data analytics has been the buzz word in the industry since long. Various industry verticals have realised the veracity of data and how past, present and future potentials could be derived from it.
What is big data analytics? Since, there has been no standard definition to understand the concept of big data and analytics. We define it as, the process of analysing the big data to uncover the hidden patterns, unknown correlations and information required for better decision making. Data has been exploding at an exponential speed which is beyond our imagination right from byte to kilobyte, megabyte, Gigabyte, terabyte, Petabyte, Exabyte, Zettabyte and to Yottabyte, which is the future for big data analytics. The data is being generated by Mobile devices, Sensor technology and networks, Social media and networks and scientific instruments. In other words, it is only us, who is generating data. But, how big is the data?, does all needs to be stored and analysed? and how to find which data points is relevant for decision making. To address the concerns, high-performance analytics becomes mandatory to distinguish the appropriate and junk data.
Here, we enter into "Big Data Analytics". For quick analysis of only relevant data, high-performance analytics has been used. Using high-performance data mining, text mining, predictive analytics, forecasting and optimization on big data enables to constantly drive effective results and drive best possible decisions out of it. In addition, various businesses have been using this technique to utilise the data for the better decision making and compete with their competitors.
Big data analytics have been used in the multiple business verticals such as e-commerce, telecommunication, healthcare, retail, energy, media and government sector as well. The big data has great potential and data scientists are using it for better insights on key business operations such as risk and fraud detection, marketing campaigns, customer retention etc. For instance, Telecommunication industry is growing increasingly, focusing on big data and is applying analytics to understand the customer history, its behaviour and to predict whether the customer is likely to churn or could be retained for a long time.
As the volume of data increases, the need and identification of automated tool becomes equally critical. Data scientist or stakeholders to identify the analytics tool that could analyse the data, highlight the issues & opportunities to focus and predict the outcomes that could help in achieving business goals.
The advantages of big data analytics could be measured by significant facts, as it enables data scientists:
We at RankOne Consulting understand the importance of big data analytics and its relevance with the multiple verticals of industry. We have been providing consulting to:
Few seminar and presentations have been conducted by our experts in various institutes to update graduates on the industry trends for big data analytics.
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