Business analytics techniques have evolved at a rapid pace, completely changing the manner in which brands and companies are functioning in almost all areas. It is therefore considered an important and essential element of all profitable and successful modern business around the globe. A major aspect of business analytics techniques is that it has an ever-evolving definition, making it difficult to implement and sustain. In a nutshell, business analytics tools is a complex combination of practices, techniques, applications, skills, and technologies that are aimed at understanding and it is also useful for analyzing business performance so that they can achieve better results and strategic goals. IIBM Institute provides Post Graduate Program in Business Analytics which help you to career growth and to learn business analytics tools and techniques.
Open Source Analytics Tools
Here are the 5 most popular open source analytics tools:
R –
R is now the most popular analytics tool in the industry. It has surpassed SAS in usage and is now the tool of choice even for companies that can easily afford SAS. Over the years, R has become a lot more robust. It handles large data sets much better than it used to, say even a decade earlier. It has also become a lot more versatile.
Python –
Python has been a favorite of programmers for long. This is mainly because it’s an easy to learn language that is also quite fast. However, it developed into a powerful analytics tool with the development of analytical and statistical libraries like numpy, scipy etc. Today it offers a comprehensive coverage of statistical and mathematical functions.
Intuitive, easy-to-use interface that’s customizable by business analysts –
Business analysts and other power users value certain features, like flexibility, in their software. For example, defining workflows, model creation and user interfaces are some of the features they value above others. The most cutting-edge business analytics tools are capable of guiding even non-technical users through the model creation process. They provide a rich contextual experience regarding data analysis options.
The ability to test advanced statistical models iteratively using machine learning algorithms –
Another criterion business analysts -and those who are a part of the decision making process- mention is the ability to define test parameters for analytics models. They said it was crucial to have machine learning-based algorithms seek optimal outcomes.This functionality is typically found in higher-end, enterprise-wide BI platforms. New tools are beginning to incorporate this functionality into apps designed for mainstream business users.
