Application of Data Analysis

Introduction

Big data analytics offers a great potential to revolution businesses. Use of analytics helps organizations achieve competitive advantage over others. Big data analytics can help companies develop products and services that appeal to their customers, as well as helping them identify new opportunities for revenue generation. Big Data analytics helps improve Customer Perception. It helps examine social media, customer service, sales and marketing data. This can help them better gauge customer sentiment and respond to customers in real time. IT Security is another area where application of Bit Data Analytics has several advantages. Any security software creates an enormous amount of log data. Applying Big Data analytics techniques to this data can help identify and thwart cyberattacks that would otherwise have gone unnoticed.

Challenges in Big Data Analytics

Implementing a big data analytics solution isn't always as straightforward as one would want it will be. There are several obstacles that can make it difficult to achieve the benefits promised. One of the biggest challenges is the explosive rate of data growth. The amount of data in the world's servers is roughly doubling every two years. Big data analytics solutions must be able to perform well at scale in order to gain anything useful from such data.
Most of the data stored in the systems is unstructured data, such as email messages, images, reports, audio files, videos and other types of files. This unstructured data can be very difficult to search – unless you have advanced artificial intelligence capabilities. These technologies are still very nascent and may not be able to perform as well as one would want them to.
The unstructured database is often a chaos because of the data supplied from various different sources. Integrating such data from all these different sources is one of the most difficult challenges in any big data analytics project. And the most important challenge, like any new technology is the reluctance to its adoption. Data Analytics looks good in magazines and whitepapers. But very few are ready to invest in its potential.

Latest Trends

Open Source

As the concept of big data analytics is catching its momentum, several open-source tools are coming up that help break down and analyze data. Hadoop, Spark and NoSQL databases are just a few. Most of the big data implementations in the commercial world are based on these leading open source technologies. That seems unlikely to change for the foreseeable future.

Market Segments

Based on the different market requirements, several big data analytics platforms have started emerging – that focus on specific domains, such as security, marketing, CRM, application performance monitoring, hiring, etc. Along with this, Analytics tools are also getting integrated into existing enterprise software at a rapid rate.

Artificial Intelligence and Machine Learning

AI is showing up as the base of Big Data Analytics. Any kind of predictive and prescriptive analysis is impossible without AI. Although the current technologies are way behind these techniques, one can guess from the pace of things that the day is not very far.
But any amount of AI or Machine Learning cannot replace the need for humans. As Big Data analytics becomes a mainstream technology, it would possibly be just another tool – a tool that can help you analyze huge amounts of data. But it would always need a human to operate and improve that tool for getting business value out of it.