Business Analyst to Data Analyst Competency (Intermediate Level)

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