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Top Data Analytics Trends You Should Know About

  • 28/05/2018
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  • Posted by Nicola
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The core of a modern and successful digital business is combined of cloud, social, artificial intelligence, analytics and associated data technologies – no doubt about that. More and more companies are focusing their attention on becoming more data-powered rather than data-generating. With that in mind, data and analytics is crucial to think about. As a modern digital company, you need to be up do date with the data analytics strategies. Here are the top ones that will most likely dominate this year. 

 

 

Augmented Analytics

One of the raising trends in the world of data is Augmented Analytics. It automates data insight by utilizing Machine Learning and Natural Language Processing to automate data preparation and enable data sharing. One of the main reasons you should consider advanced analytics and augmented data preparation for any enterprise is the fact that it advances in smart data discovery and other techniques which can have a positive impact on your ROI. The augmented data preparation and related tools will improve data popularity, data literacy and even user adoption

 

 

IoT Analytics

IoT has been a big player in 2017 and will continue to expand this year too, with more and more devices getting connected. Industries like healthcare, retails, supply chain an other have been using IoT to boost ROI, this year we can see a high increase in the number of of companies that use IoT for more personalized marketing efforts.

 

 

Cloud For Big Data Analytics

Cloud can provide infrastructure, platform, and software resources as services to big data. As cloud provides elasticity and expertise for accessing data and it can derive value from it. Companies are making use of big data analytics to determine business trends and insights from the volume of data created. Organisations can use cloud infrastructure to improve risk and maintain control by analyzing load, cost and security etc.

 


 

Apache Spark and Flink

Apache Spark is on our list. Its big data processing engine that will be used for loading the data lake and machine learning training and prediction jobs. While Spark uses micro-batches to enable fast processing, Flink on the other hand  is a true streaming engine that can also do batch processing by treating a stream of events as a data set with a beginning and an end.

 

In summary, it has been a big year in the world of data analytics. There is no doubt this year will become even greater that is why it is crucial for companies to be up to date and catch up with the speed of constantly evolving data analytics. 

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