And it also has a huge community of developers for support. With the help of R, it is easy to perform data manipulation with packages such as plyr, dplyr, and tidy. It is excellent when it comes to data visualization and analysis with packages such as ggplot2, lattice, plotly etc. It is an open-source programming language. R is one of the most popular languages for statistical modelling, visualization, and data analysis. The data analytics tools listed below are in no particular order. How do we decide which data analytics tool to choose? This blog talks about the top data analysis tools that one can use to increase efficiency. A data analyst’s key responsibility is to gather insights from data and to do so, they must make use of the various data analytics tools available to them. The information could be vital in making data-driven business decisions. To solve the purpose of converting or transforming raw data into valuable information and to work on data analysis projects, there exist multiple Data Analytics tools in today’s world.
It is everywhere, Data analytics in Finance, eCommerce, Media, and what not. Data Analysts are making use of this data on a regular basis and thus the advent of Data Analytics. This data is extremely helpful in making important business decisions, gathering insights, and providing data-based solutions.
The data being generated on a daily basis has increased massively over the years, with close to 2.5 quintillion bytes generated on a daily basis.
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