Business Analyst to Data Analyst Competency (Intermediate Level)

  • 25m
  • 25 questions
The Business Analyst to Data Analyst competency benchmark will measure your ability to recall, recognize, and understand concepts and techniques applied as a business analyst working with Excel, Tableau, and Power BI. You will be evaluated on your ability to recognize business analytics techniques and functions in Tableau, Power BI, and Maria DB; create basic data visualizations using charts; create dashboards; load data from files in Tableau; analyze tables; apply transformations, data validation, and cleaning; and use pivot tables. A learner who scores high on this benchmark demonstrates that they have the required skills in business analytics to build effective dashboards and share reports and insights with business users.

Topics covered

  • analyze your data at a higher level and drill down to a lower level based on a date field
  • create a foreign key relationship (a.k.a., a referential integrity constraint) between two tables in Power BI
  • create a relationship between two tables in Power BI and enable automatic detection of these relationships
  • define a field in your dataset which is based on a calculation performed on an existing field
  • develop a story to convey information in the form of visualizations by assembling charts and a dashboard
  • gather detailed information from Tableau charts by interacting with them
  • generate multiple charts based on the same dataset for use in a dashboard
  • illustrate the process involved in performing classification when a decision tree model is used
  • implement ANOVA (Analysis of Variance) using Analysis ToolPak to analyze variances within and between groups  
  • implement joins using the join() method
  • import JSON data into Power BI and use Power Query to convert JSON data into tabular data and change the column data types
  • import XML data to Power BI, filter it, change the data type, and find and delete rows with errors
  • load data from a variety of sources into BigML in order to train and evaluate machine learning models
  • perform conditional filtering using the query function
  • perform some basic data cleaning on your datasets using the Tableau data interpreter
  • perform various advanced Power Query operations, such as removing columns and Top N and error rows, performing row filtering operations, and creating grouped bar charts
  • plot country-related information on a Tableau Map
  • portray different characteristics of your data by using a variety of charts available in Tableau
  • recall the various metrics used to evaluate the quality of a machine learning model
  • recognize the purpose of clustering algorithms and list some of their use cases
  • use Analysis ToolPak for histogram analysis and descriptive statistic computing, compute ranks and percentiles, and perform both random and periodic sampling  
  • use BigML to build an ensemble of decision trees to solve a classification problem
  • use pivot tables to explore data
  • use Power BI to design a stacked bar chart for data visualization and fields with large numbers of unique values and create a basic filter using the filters pane
  • use the Power BI Report View to visualize data that has been imported from an Excel spreadsheet and instantiate a matrix visualization in the report view