10 Data Science Tools That You Should Learn

Good programming skills are essential to working in the field of data science. It deals with Boolean logic, functions, and higher analytical skills to understand how to manipulate and program the code to make it functional.

Tools for the non programmers

Most of these tools have a GUI interface and are easy to learn by anyone who does not have a programming background. Every industry uses these tools to make their jobs related to data science efficient and easy.

1. Rapid miner is an open source tool that helps in visualizing data, handling data analytics and statistics.
2. Data robot is automated software that is used for text mining, scaling, and transforming raw data into a usable one.
3. BigML is used for making blueprints of models that can be used for various purposes. They have inbuilt algorithms for detection of anomalies and clustering of data.
4. Google Cloud Prediction API is used to analyze comments and mails for spam detection. It also gives insights on the amount of data a user uses every day.
5. Paxata is used to group and aggregate data. It adds data from a variety of sources. It also combines various data for best output with a single click.
6. Trifacta is a standalone application that is used in data preparation. It gives shape to raw data and resolve anomalies. This is used across life science and financial industries.
7. Narrative science is used to collect the statistics of data and generate reports specific to the data. An organization can use this to display trends making use of past data.
8. MLBase is an algorithm based open source software that can be used for searching data. They are used to collect abstract data and provide relevant search results.
9. WEKA is software that is used for data mining. It is GUI based and is used by beginners.
10. DataRPM is software for making predictive models and does not require coding.

Conclusion

You don’t need to have a technical background to be a data scientist, as here are many data tools that can be used to sort data and work in these fields which do not require extensive programming knowledge.