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    Categories: Tech & Trends

Advanced Analytics: The Next Generation of Big Data

By Timo Selvaraj,Co-Founder & VP Product Management,SearchBlox Software, Inc.

Analytics change the way companies operate and serve. The main purpose of data analytics is to provide business value.

 2015 was a significant year in the big data world. Businesses have realized that making the best decisions is only possible when data in all forms and sizes is rightly processed. They have understood that the unstructured data has to be managed to extract intelligent business information. As advanced analytics can transform big data into smart data, giving insight to the businesses and adding real industrial value, IT professionals are heading towards it. Additionally, it involves sophisticated tools and techniques like data/text mining, machine learning, sentiment analysis, forecasting, visualization, pattern matching, semantic analysis, complex event processing, graph analysis etc. Utilizing the real value of big data, IT leaders and businesses are boosting investment in advanced analytics.

Analytics Reinvents IT Industry

There is no single industry that has escaped from digital data. Most of the major organizations, whether public or private, have huge data repositories containing valuable information about their customers and service users. Businesses from a range of sectors thus have incorporated analytics to help them understand their customers and improve their performance. Organizations are choosing analytics to come up with a more proactive approach to predict future demand, take the best course of action, reduce risk and improve outcomes.To put this in perspective, consider Facebook’s Topic Data. Last year, Facebook introduced Topic Data that uses text analytics to make the marketers aware of the opinion of their audiences.

eCommerce

In eCommerce, Text analytics helps in developing a better understanding of the likes, dislikes, and motivations of the customers. It has been utilizing the voice of customer analysis and social media analysis to analyze the customer psychology to deliver a high-level customer experience.

Healthcare

Similarly, healthcare is also overwhelmed with volumes of diversified information. Analytics can manage such large and complex electronic health data sets with higher accuracy as compared to the traditional methods. With analytics, medical centers are using patient profiles for seeking benefits that the patients can get through preventative care and lifestyle changes.

Text Analytics taking Industry to the Next Level/ Text Analytics in Government

Although data analytics are mostly used by enterprise companies, the rise of big data and the need for greater insight hasn’t been limited to the private sector. The government has also put a step forward to unlock insights hidden in their data repository. They have been using advanced analytics to drive down costs, improve efficiency, and uncover unexpected correlations. For example, the taxation department can utilize data analytics for fraud detection and anti-money laundering activities to get accurate findings. In order to detect the fraud, the organization needs to look at every transaction meticulously. Analytics performs effective internal monitoring with established parameters, across applications and system to detect the fraud.

The Business Value of Text Analytics

Companies need a strategic plan for gathering and organizing data. A system is necessitated that aligns with business strategies and methods that can create values and insights for improved results using the available information. That is when analytics come to the rescue. Companies should adopt machine learning and AI within their own systems to simplify the way they have been dealing with the huge amounts of information.

With advanced analytics, the big data can be processed, stored and mined without human intervention, addressing critical business problems and providing business benefits far beyond the conventional BI. Thus, advanced analytics can be the ultimate tool for modern data-driven organizations.

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