A data scientist needs to have the following 7 skills are as follows-

  • Database knowledge

Gaining database knowledge is require to store and analyze data oracle database SQL Server MySQL and Terra data are some of the tools that are required for this.

  • Statistics

Learning statisticsprobability and mathematical analysis statistics is the science concerned with deploying and studying methods for collecting analyzing interpreting and presenting empirical data skill.

  • Programming

Mastering one programming language, programming tools such as our Python and SAS are very important to perform analytics and data R is a free software environment for statistical computing and graphics it supports most machine learning algorithms for  data analytics like regression, Association, clustering and so on. Python is an open-source general purpose programming language libraries and such as numpy in sci-fi are used in data science. SAS can mine alter manage and retrieve data from a variety of sources. It can also perform statistical analysis on the data skill.

  • Data wrangling

Learning how to wrangle data up data wrangling involves cleaning data manipulating data and organizing the data. Some of the tools that are used are arc Python flu scoop skill.

  • Machine Learning

To master the concepts of machine learning, machine learning provides systems the ability to automatically learn and improve with experience without being actually programmed to do that. Machine learning can be achieved through number of different algorithms like regression nave base SVM K-means clustering cannan decision tree just a name of your skin.

  • Big Data

Having working knowledge of big data tools, big data is a term that is used to describe large and complex data. It cannot be dealt with traditional data processing software. Some of the tools that are used or software’s that are used are apache spark, Hadoop, Talend, Tableau, Splunk and so on.

  • Data Visualization

To develop the ability to visualize the source data visualization involves integrated different data sets, analyzing models and visualizing them in the form of diagrams, charts and graphs. Some of the tools or software that are used are tableau click view power bi and Google Data studio.

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