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A data scientist requires large amounts of data to develop hypotheses, make inferences, and analyze customer and market trends. Basic responsibilities include gathering and analyzing data, using various types of analytics and reporting tools to detect patterns, trends and relationships in data sets.
In business, data scientists typically work in teams to mine big data for information that can be used to predict customer behavior and identify new revenue opportunities. In many organizations, data scientists are also responsible for setting best practices for collecting data, using analysis tools and interpreting data.
The demand for data science skills has grown significantly over the years, as companies look to glean useful information from big data, the voluminous amounts of structured, unstructured and semi-structured data that a large enterprise or internet of things produces and collects...
Education, training and certifications
The education requirements for data scientists typically include an advanced degree in statistics, data science, computer science or mathematics. There are a number of certification opportunities for this role, including Dell EMC DECA-DS, MCSA: Various SQL/Data Engineering Options, Microsoft MCSE Data Management and Analytics, and Certified Analytics Professional...
Education.
Data scientists usually have at least a bachelor's degree in mathematics, data analytics, computer science or statistics. On the other hand, citizen data scientists might have a wide variety of educational backgrounds, but have experience with analytical tools and software that makes them better able to create models and perform complex analyses without a formal education in the aforementioned fields.
History of data science
Concise survey of computer methods |
Naur in 2008 Photo: Wikipedia, the free encyclopedia |
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Source: WhatIs.com