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Updated in [April 29th, 2023]
What does this course tell?
(Please note that the following overview content is from the original platform)
Learn Tableau and Visualization
What you'll learn:
Connecting to various data sources, and cleaning up data
Joining multiple datasets (Union, Blending, cross database Joins and many more)
Visualizing the data as Charts, Graphs, Maps, Plots etc.
Tricks and tips to tell a simple and effective story using data.
The concept of Tableau Database or Fast engine (Extracts)
Visual Analytics, Drilldowns, Sorting, Grouping, Set and Cluster creations, Filtering of data, Parameters, Tooltips, Annotations, Reference lines
Enhancing or switching your career in the field of Data Science and Analytics
Packaging your report into a Dashboard.
Playing with Geographical data types and using Maps in Tableau
Writing very complex and powerful calculations like aggregate calculations, Date, Logical, String, Number and other types of calculations.
And many more.
Are you looking to learn visualization for your next job as a data analyst or data scientist? If so, I have got a new course for you. I have recorded a series of videos to learn visualization using Tableau. You will learn, how to connect to different data sources like excel, SQL server and other databasesinvery less time, without needing to know complex coding and quickly clean up the data and put together powerful visualization. We will look at various examples to take complex data and visualize a simple story using the power of graphs and charts.
What will you gain from this course?
I am a coder and a manager and run a Data science team. Quite often through Linkedin and other channels I get questions on tips to start a career in Databases and Analytics. So I put together this course. I have taken into consideration a lot of stuff, that you will often need if you decide to start a career as a Reporting Analyst or Data Analyst.
By the end of this course, you will have a good understanding of Tableau, how to use it, how to gather data from different data streams and clean them, how to use the various tools provided by tableau in-order to create a report or visualization and many more. In short, you will be apply to directly apply these concepts in your new job or day to day work.
You will be able to take a very complex data and transform that into a beautiful story for analysis and present it to leadership.
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
Connecting to a variety of data sources and cleaning up the information.
combining several datasets (Union, Blending, cross-database Joins, and many more).
Data visualization takes the form of charts, graphs, maps, plots, and so on.
Tips and tricks for using statistics to tell a clear and effective tale.
Tableau Database or Fast Engine is a concept (Extracts).
Developing or changing your career path in the areas of data science and analytics
Drilldown, sorting, grouping, and the development of sets and clusters are all examples of visual analytics. Parameters, Tooltips, Annotations, and Reference Lines are all examples of data filtering.
Create a dashboard out of your report.
Tableau: Using Maps and Playing with Geographical Data Types.
Calculations such as aggregate calculations, Date, Logical, String, Number, and other sorts of calculations can be written in a very complicated and sophisticated manner.