data analytics courses

Introduction

Data Analytics is one of the powerful techniques that use raw data to enhance the productivity of humans and sales of business establishments and companies. In a nutshell, Data analytics involves the extraction of useful data from raw data, the categorization of data for easier identification and analysis for certain patterns and overall properties to finally provide productive results. These results are usually used to enhance the performance of a particular product or service. As the name suggests, Data Analytics is the analysis of data that has been achieved from the common masses. During analysis, a number of patterns and techniques can be found which might help humans in other conventional ways.

Importance of Data Analytics

Data Analytics has a number of advantages which become very important from the business perspective as the techniques of Data Analytics provide us with the following results:

●       Help to improve Business Requirement by studying customer sales patterns and their subsequent queries related to the same

●       Helps to Understand the Market related to a particular product and the performance of the competitors of the same

●       It helps to generate and understand reports for different departments of a business organization. These reports can be used for further analysis and comparing with past reports for better performance by a particular department.

●       Help to collect and analyze data insight from raw data collected

Tools in Data Analytics

There are a number of tools within Data Analytics that are provided with different functionalities:

●       Apache Spark is basically a database engine that is used for machine learning model development and data pipelining.

●       OpenRefine is a data cleaning software that eliminates unnecessary data to extract useful data and use it for analysis. This software is also known as GoogleRefine and is used to clean data after combining the same data from multiple resources.

●       Konstanz Information Miner (KNIME) is a data analytics platform that is used to create data models after a thorough analysis of the same. Using the concepts of Data Pipelining, this software cleans data, analyses it, questions the presence of certain bits of data and then creates a model using the same.

●       Python is the most widely used computer programming language that provides users with Data Visualization and Machine Learning Libraries to work with. Some of the libraries are TensorFlow, MatPlotLib, Pandas, and Keras.

●       R Programming is the best language that is used for data modeling and statistical programming. All packages can be automatically downloaded with this language.

●       Tableau Public is free data software that helps users to create dashboards, data plots, data graphs, data maps, and visualizations.

●       SAS is the popular programming language that can be used for data manipulation and statistical programming.

Resource Box

We hope that this article was able to pique your interest in Data Analytics and you will do some research on your own to know more about this amazing technology, which is truly revolutionizing the way we look at the data and use it to help us for the future.

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