Top 10 tools for working with big data for successful analytics developers

The importance of data in today’s business is difficult to overstate because no meaningful decision can be made without the analysis of relevant data. The data analysis not only drives the decision making but also takes an active part in developing strategies and methods that ensure the existence and success of organizations. Earlier, entrepreneurs used to call data analysis “business intelligence,” which perfectly characterizes the essence because data could provide a competitive advantage to those who used and interpreted them properly.

Nowadays, a new term for referring to business intelligence was coined: “big data.” This name also makes a good sense because since the times of “business intelligence” the volumes of data became incredibly large. As the result, more effort should be applied to deal with them and make it useful for analytics professionals.

In this article, we have compiled a list of the top ten big data tools that are used by successful analytics developers.

1. Cassandra

This tool is widely used today because it provides an effective management of large amounts of data. It is a database that offers high availability and scalability without compromising the performance of commodity hardware and cloud infrastructure. Among the main advantages of Cassandra highlighted by the development are fault tolerance, performance, decentralization, professional support, durability, elasticity, and scalability. Indeed, such users of Cassandra as eBay and Netflix may prove them.

2. Hadoop

Another great product from Apache that has been used by many large corporations. Among the most important features of this advanced software library is superior processing of voluminous data sets in clusters of computers using effective programming models. Corporations choose Hadoop because of its great processing capabilities plus developer provides regular updates and improvements to the product.

3. Plotly

Successful big data analytics use Plotly to create great dynamic visualization even in case if the company does not have sufficient time or skills for meeting big data needs. It makes the process of creating stunning and informative graphics very easy using the online tools. Also, the platform enables sharing the findings by transporting the results into different convenient formats.


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