The occupational utility of Data Analytics is of no ambiguity to any industry. There are a plethora offields which can harness the...

DECODE THE FUTURE - Forthcoming DA trends of 2017

April 28, 2017 Libsys Blog 14 Comments

analytics



The occupational utility of Data Analytics is of no ambiguity to any industry. There are a plethora offields which can harness the immense potential of analyzed data to tailor customized solutions to each challenge they face at varied fronts for instance, from issues of logistics to telecommunication. The business organizations are investing heavily to dig deeper into very large data sets in the quest of finding different answers to implicit problems of hardware, software or services.  

What is 2017 set to deliver? Let us acquaint ourselves with forthcoming trends of Data Analytics to combat the summons of the future with next generation solutions.

Data Monetization 

The ultimate goal of the operations of an established company is to explore through its existing resources and discover the maximum number of lament sources of creating revenue. The key idea is to employ what is already present than creating an entirely new arm. Libsys helps in transforming the data from liability to an asset for your company.

Serving the need of the hour, visionary companies are participating in the tedious yet benefiting process of monetization of data. The data which had long been used for predictive analytics is now the new raw material to create revenue. The process follows a schematic flow of aggregating-attributing-validating-exchanging data, driven with a scouting sense of analytics to solve almost all operational concerns.

Bridging the impossibilities through AI (Artificial Intelligence)

The year 2017 is expected to witness a sweeping comeback of Artificial Intelligence. Assessing various factors simultaneously to converge into a one step customized solution in a considerably small time is what made AI return to the arena.

For instance, a technology company can dive through the data collection of factors like customer proximity, regulatory compliance, logistics, manufacturing, and other estimations churned into a customized AI model to come up with a cognitive solution to the problem being addressed.

Fixing Revenue Fissures

Organizations serving an extensive range and volume of customers like hospitals, pharmaceutical companies or healthcare providers are more likely to opt to focus on measures of fixing the leaks in revenue instead of creating new models to collect more data and data processing models.

Targeted research models will expectedly override the predictive models this year as they save a large chunk of time and money. After all, saving equals creation.

Concurred Blockchain and Data Analytics

Data Analytics complements Blockchain as it needs to counter both quantity and quality. While the blockchain form the very base of intricate financial systems like digital payment gateways, transaction of virtual currencies etc. 

With customer satisfaction at stake blockchain are highly likely to be witnessed converging profoundly with Data Analytics. As a result of which the massive customer base of companies in the sector of banking and financial services shall see a steep improvement in grade of service. Retail and logistics industry is estimated to opt and benefit alike from Data Analytics this year. 

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