What Are The Different Tools Used In Data Science?
Data science uses various tools, algorithms, and machine learning concepts to extract hidden patterns from unstructured data. How does this differ from the work that statisticians have been conducting for years?
A data analyst typically uses the data's historical processing to describe what is happening. However, a data scientist uses various sophisticated machine learning methods and exploratory analysis to predict the occurrence of a specific event in the future. A data scientist will examine the data from various viewpoints, often from previously unknown ones. To learn more about data science, join Data Science Training in Chennai.
Data Science tools used for data science are:
1) Apache Hadoop:
A free, open-source system called Apache Hadoop can manage and store enormous amounts of data. Massive data sets can be distributedly computed over a cluster of thousands of machines. It is used to process data and perform complex calculations.
2) Microsoft HD Insights:
Microsoft offers Azure HDInsight, a cloud platform for analytics, processing, and storage. Businesses use Azure HD Insights like Adobe, Jet, and Milliman to handle and manage enormous amounts of data.
3) Informatica PowerCenter:
Informatica's sales have rounded off to about $1.05 billion, which explains why the company is receiving so much attention. Many of Informatica's products are geared toward integrating data. But because of its ability to integrate data, Informatica PowerCenter stands out.
4)RapidMiner:
One of the most widely used tools for applying data science is RapidMiner. The Gartner Quadrant for Data Science Platforms, the Forrester Wave for Predictive Analytics and Machine Learning, and the G2 Crowd Predictive Analytics Grid, RapidMiner, was ranked first. To learn more about RapidMiner, join the Best Online Data Science Courses.
5)Tableau:
The most widely used data visualisation tool on the market is Tableau. It enables you to transform raw, unformatted data into a format that can be processed and understood. Using Tableau's visualisations, you may quickly comprehend the dependencies between the predictor variables.
6)Qlikview:
More than 24,000 enterprises worldwide utilise QlikView, another data visualisation platform. It is one of the best tools for visualising data to gain insightful business information.
7)DataRobot:
DataRobot is an automation tool powered by AI that facilitates the creation of precise predictive models. A variety of Machine Learning algorithms, including clustering, classification, and regression models, are simple to deploy with DataRobot.
Conclusion:
In this article, you will gain some insight regarding what are the tools used in data science.To learn more about different tools used in data science, join the Data Science Courses in Bangalore.
