5 Prominent Big Data Analytics Tools to Learn in 2020
Well, if there is one mantra that seems to be playing on the lips of everyone who has even a fleeting interest in technology and all its wonders, it should be Big Data! Just how big is Big Data? Let us explore this bit a little:
- Some 3.5 billion searches are made on Google every day
- More figures about Big Data: When organizations fail to use their data, it costs them 10 to 20 percent of their total revenues
- Data produced in 2020 will outnumber that produced in 2009 by 4400 percent
So, what does all this mean for businesses? Is Big Data all about only numbers and academic research of these numbers? If it were just that, no one would have given a damn about it. Truth is, this data is the goldmine for businesses. This data, which in itself is useless, can make a life and death difference to organizations.
- When organizations fail to properly use this data, businesses and the government can cost the American economy a loss of a whopping $ 3.1 trillion
- Increasing data accessibility by just 10 percent can shoot up the annual income of an average Fortune 1000 company by as much as $65 million a year
- A retailer can increase its potential by increasing its operation margin by over 60% by using Big Data Analytics effectively.
So, here we are. This shows the acute importance that Big Data Analytics has for organizations worldwide. So, which are the tools that help companies harness their Big Data effectively? Let us look at 5 prominent Big Data Analytics tools to learn in 2020:
Its ease of use and accessibility make it a preferred big Data Analytics partner for many organizations. Where this platform stands out is that it integrates with the Azure Data Lake Storage Gen2, which supports Hadoop Distributed File System, an aid in high level Big Data Analytics.
Employing the CQL (Cassandra Structure Language) to interact with the database, Cassandra from Apache is Open Source and free. It offers a high degree of availability, as huge volumes of data are spread across several commodity servers. It stands out for its reliability and its ability to handle huge amounts of data.
Known for its ability to simplify and automating data integration, Talend enables smarter data quality through the use of Machine Learning and NLP. It also streamlines DevOps processes.
KNIME is very useful in analyzing, manipulating, and modeling data using visual programming. In supporting many programming languages, it is a great tool for integrating many aspects of Machine Learning and data mining.
The real forerunner of this field in that SAS Visual Analytics was carrying out analytics long before the term came to be coined, SAS Visual Analytics comes with advanced tools for deep analytics that has drag and drop functionality with which to build attractive and insightful visualizations.
Conclusion
So, with so much on offer as far as Data Analytics tools to learn in 2020 are concerned, there is a wealth of information available for those who want to make a career in Big Data Analytics. We request you to take a look at some of Simpliv’s online courses on big Data Analytics, which will open up avenues for learning and for making rapid progress in you careers.
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