Tools for Analytics

Using Machine Learning and Artificial Intelligence

Photo by Mitchell Luo on Unsplash

By tools for analytics, the reference are to apps that allow for environments to create solutions, language, libraries, and even graphical user interface to manipulate data for insights from information. There are many tools for data analytics. What is available?

Tools

Anaconda provides environment for Python and R including machine learning for mac/linux/windows. After downloading the app and installing, the environment can be customized to include variety of data science tools with libraries. Anaconda is used desktop but also exists as a cloud version.

JetBrains is an organization with a lot of apps for specific goals. There is PyCharm for Python, DataGrip for Databases, RubyMine for Ruby, and more. For analytics, the tool set and ability to integrate across their tools is unique. The positive is creating full apps that have artificial intelligent components or subcomponents and code for other pieces of the app in languages like PHP that can work together in a JetBrains solution.

Google has a few analytics tools, most notably, Looker and Google Cloud Platform.

Microsoft Access, Azure, Excel, and Power BI all provide analytics and data service.