Data Science – Business favor or bald?

2019-04-30 Education No comment


  • In general, some facts, sets of information, or details used to plan, organize, and analyze certain things are called data.

  • When it comes to knowledge through some experiments and observations, it is science. The process of learning skills in a particular area is training.

  • Summarizing all three terms, we get a phrase called Data Science Training, which means that training allows people to store historical data and accurately predict patterns.

Why do you need it?

  • Because it is a combination of database management, data analysis, predictive modeling, machine learning, big data distributed computing, coding, data visualization and reporting, it is very important.

  • Business strategy is built on top of data analysis, not raw data, so data training is required.

How does the training process move forward?

  • Initially no analysis is required, so the first steps include clear basic statistics, excel and SQL, software such as SAS, R, Python [for encoding, such as mean and median] Hive and Pig most data scientists.

  • Further steps include understanding data cleansing, data processing, data analysis, forecasting knowledge and software such as Hadoop, Tableau, Qlikview, Spark and Spark SQL.

  • The final step includes machine learning techniques, unstructured data analysis techniques, and the use of learning blog data tools.

  • Once the training is completed, covering all of the above, individuals can become data scientists.

The difference between business intelligence and data science and the reasons for data science! ?

  • Usually, the above two terms are used synonymously, and there is a difference between business intelligence and data science.

  • Business intelligence is a traditional approach that involves only two business issues, what is happening? Why is this happening?

  • However, data science deals with these two issues as well as modern methods to solve what is going on now? What should I do?

  • Therefore, it is clear from the above details that alternative terms [considered!] are different in their own type!

  • In addition, content display data science is chosen through business intelligence because business intelligence is only descriptive and diagnostic, with the former being descriptive, diagnostic, predictive, and normative and practical.

shut down:

  • Data Science can be used for route planning for any of your business, and these businesses will show how your business can continue to grow and gain momentum.

  • Second, you can perform predictive analysis to know what you can do with reference to various factors in the future.

  • Companies can use data science to perceive their perceptions, plan ahead for promotional offers, future needs, next reorder time, and consumer-related content.

  • Finally, it can be noted that with the help of data science, it is really easy to determine which resources can perform better and which resources can be used to perform better.

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