Data Analysis Software – Add Value to Businesses and Improve Productivity

Businesses, in order to excel in their operations, need to make an informed and timely decision that usually depends on the available data. Though, the most difficult thing for any organization is the retrieval and analysis of relevant data to have vital insight that can be aptly used in decision making. Therefore, decision making in businesses often relies on the available data that need to be current, accurate and reliable. Data need to be authentic so that it can be aptly analyzed to gain vital business insight, which can be further used in decision making. Data analysis is a procedure through which data is inspected, cleaned, transformed and modeled with the aim to gain vital information, suggest conclusions, and support decision making in businesses.

Advancement in technology has allowed software developers to develop cutting-edge data analysis software, which makes it easy to retrieve, interact and analyze the data for businesses with the sole intention of improving their products and services. Data analysis software has the statistical and analytical capability to inspect, clean, transform and model data with an aim to derive vital information for decision-making. Using this software, businesses can explore the available data, understand and analyze complex relationships of data. Besides statistical analysis, this software also has powerful visualization capability that allows businesses to share data with other stakeholders. The software is designed to allow users to quickly analyze a large amount of data.

Best and Popular Data Analysis Software

R - R is a highly popular data analysis software used in quite a large number of businesses. The software has become a lot more robust and versatile and handles large data sets much better. The success of this analysis software can be contributed to the fact that it has well integrated with many big data platforms.

Python - Python has been a favorite analysis software of programmers for long mainly because it is easy to learn language that is also quite fast. Due to the development of analytical and statistical libraries like scipy, numpy, it developed into a powerful analytics tool. Currently, it provides comprehensive coverage of statistical and mathematical functions.

Apache Spark - Spark is another open source software that is built with a focus on analytics, especially on huge volumes of data or unstructured data. In the last couple of years, Spark has become hugely popular, mainly because of easy integration with the Hadoop ecosystem. Besides, it has its own machine learning library that makes it perfect for analytics as well.

SAS - SAS is a popularly used analysis software in the industry in spite of being a paid analytics software. It is a robust, versatile and easy-to-learn software that has added tons of new modules. Specialized modules of SAS that have been recently added are SAS analytics for IOT, anti-money laundering and SAS Analytics Pro for midsize businesses.

leading and cutting-edge data analysis software has eased data retrieval and analysis for deriving important information for decision making. Even small and midsize businesses are increasingly using this software to explore available data and to quickly analyze relationships of data that help them in making crucial decisions for the business.

I love writing a lot and currently working as a Content and Academic Writer. My writing is qualitative, professional and timely which my clients like about me.