#### Overview of this book

The Tableau Certified Data Analyst certification validates the essential skills needed to explore, analyze, and present data, propelling your career in data analytics. Whether you're a seasoned Tableau user or just starting out, this comprehensive resource is your roadmap to mastering Tableau and achieving certification success. The book begins by exploring the fundamentals of data analysis, from connecting to various data sources to transforming and cleaning data for meaningful insights. With practical exercises and realistic mock exams, you'll gain hands-on experience that reinforces your understanding of Tableau concepts and prepares you for the challenges of the certification exam. As you progress, expert guidance and clear explanations make it easy to navigate complex topics as each chapter builds upon the last, providing a seamless learning experience—from creating impactful visualizations to managing content on Tableau Cloud. Written by a team of experts, this Tableau book not only helps you pass the certification exam but also equips you with the skills and confidence needed to excel in your career. It is an indispensable resource for unlocking the full potential of Tableau.
Chapter 2: Transforming Data
Chapter 3: Calculations
Chapter 4: Grouping and Filtering
Chapter 5: Charts
Chapter 6: Dashboards
Chapter 7: Formatting
Chapter 8: Publishing and Managing Content
Chapter 9: Accessing the Online Practice Resources
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# Fixed Level of Detail Calculations

Fixed level of detail calculated fields are fields that fix an aggregated value to the level of specified dimensions as opposed to the measure being aggregated to the dimensions on the view. Fixed level of detail calculations are written in the following format:

`{ FIXED [Dimension1], [Dimension_n] : AGG([field]) }`

As many dimension fields as needed can be included before the colon and these will specify the level of aggregation to fix the measure at. If no dimensions are included in the fixed level of detail calculation, then the aggregation will be fixed across the whole dataset.

An aggregation is always required and this can be any aggregation (`SUM`, `AVG`, `MIN`, `MAX`, and so on) and the field being aggregated does not necessarily have to be a measure. For example, the maximum date per customer could be found and fixed at that level and then used in the view without needing to bring the customer field onto the view.

The fixed level of detail...