With big data skills fit for the application: 7 easy steps to data professional


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Data analysis skills are very popular with employers. But appropriate training and further education are still rare. Hence 7 tips on how to become a data analysis expert even in a short time further education can.

Fit for application with Big Data Skills: 7 easy steps to becoming a data pro With Big Data Skills fit for application: 7 easy steps to becoming a data pro

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Here writes for you: Lars Milde is Senior Marketing Manager DACH & Eastern Europe at Tableau Software. Profile

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Data Analysis - Most Wanted 2017 Skills

Overview

Data analysis and visualization include 2017 as one of the ten most sought-after skills among employers. This is the social network LinkedIn 2017 calculated on the basis of surveys.

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Many would like to do an appropriate training or further education, but corresponding offer are unfortunately still quite rare. It only helps to adapt the skills themselves in self-government.

7 steps to the data pro

Overview

Here are seven tips on how you can develop yourself to the data specialist without great effort:

  1. Use self-service tools: Working with data is already the order of the day in many companies. In order to evaluate data, you do not need to be a statistician or data scientist. Modern self-service tools help you to easily analyze your data and visually prepare it. You can train in such training courses. On the net there is also free help - in the form of training videos and blogs.
  2. Improve analytical skills: Just as important as the safety in using technical tools are corresponding personal competences. If you get used to critical thinking and analytical curiosity, you will be able to draw more from the existing data - and of course improve your own soft skills.
  3. Ask questions: Questions are an important prerequisite for analytical thinking. Only through specific questions to the data can this gain insights. With the help of interactive data dashboards, you can ask questions to the data live and in collaboration with your colleagues and answer them in real time. The answers to the original questions often reveal completely new aspects that lead to new insights. The method of "5 questions", developed by the Japanese Sakichi Toyoda, can help: Here, each response is responded to with a new "why" - until you get to the root of the problem.
  4. Facts instead of feeling abdominal: Your supervisor asks you for your opinion on a topic? Then do not lead your answer by saying "I feel like ...". Sovereign and competent acts a data-driven answer - such as: "My data tell me that ...".
  5. Practice creates masters: The Internet provides an almost unlimited amount of freely available data that you can use to experiment and visualize. Free tools such as Tableau Public also allow you to make your own data and visualizations available for download or to save them as a link in personal profiles -Casting insert.
  6. Enter with entertaining data: When you go into data analysis, you start with data on entertaining issues, such as the question of whether movies are getting better and better with the growing experience of the directors (see graphic). Simple records and fun on the subject provide faster initial success.
  7. Learn from the community: Feedback is important. On the Internet, you will find other newcomers, as well as professionals, with whom you can network and share information. Also relevant blogs - for example the visualization adviser of Andy Cotgreave - help you overcome initial hurdles.


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