![]() A key step to prepare data for analysis includes using multiple different data sources by establishing relationships between them, creating joins, union of tables, and blending data. A candidate is expected to perform cleaning operations, and also organize data into folders. It is required to assess data quality for completeness, consistency, and accuracy. Preparing the data for analysis is also critical for the Tableau Data Analyst Certification Exam. A candidate taking the Tableau Data Analyst Certification Exam is also expected to pull data from relational databases by using custom SQL queries, connecting to data sources on Tableau Server, and replacing the connected data source with another data source for an existing chart or sheet. Hence you a candidate is expected to be aware of how to connect to extracts, spreadsheets, hyper files, and tde files. The benefits of Live vs Extract data sources and which type of data source is preferred in which scenario is a key topic to understand. You are required to be aware of how to connect to different data sources. The Tableau Data Analyst Certification Exam has 24% of the questions from this section. Top Employers recognize the Tableau Data Analyst Certification Preparing for Connect to and Transform Data using Tableau This is definitely one of the finest Certification Exams that Tableau has to offer and regularly leads to a salary hike during new hirings. The fact that the Certification includes questions using Tableau Server, Tableau Prep, Tableau Online, Tableau Desktop, indicates the test does a comprehensive assessment of knowledge of the Tableau Software as a whole. Besides the fact it is provided by Tableau, one of the leading Data Analytics organizations in the industries today according to the latest Gartner report, the Tableau Certified Data Analyst Certification Exam essentially evaluates a candidate on all the essential key skills that a professional must have. The Tableau Certified Data Analyst Certification is one of the most highly recognized certifications in the Data Analytics industry today.
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