Business Analytics for Business Managers

Clear and concise structure: Learn how to organize your report with a clear and logical structure. Use sections, pages, and visuals to present information in a way that is easy to navigate and understand.

Visual hierarchy: Utilize visual hierarchy to guide users\' attention and emphasize important information. Arrange visual elements based on their relative importance and using formatting options such as font size, color, and formatting to highlight key insights.

Consistent theme and branding: Apply a consistent theme and branding to your report. Using color schemes, fonts, and logo placement that align with your organization\'s brand guidelines to create a cohesive and professional look.

White space and alignment: Using white space strategically to improve readability and avoid clutter. Ensure proper alignment of visuals, text, and other elements to create a neat and organized appearance.

Grids and guides: Using grids and guides to align visuals and maintain a consistent layout throughout the report. This helps create a clean and structured design.

Visual selection and formatting: Choose appropriate visualizations based on the type of data and the insights you want to convey. Apply appropriate formatting options such as colors, labels, tooltips, and data labels to enhance the clarity and visual appeal of your visuals.

Drill-through and interactivity: Utilize drill-through functionality and interactive elements to enable users to explore data in more detail. This allows users to interact with visuals, drill into specific data points, and gain deeper insights.

Report navigation: Implement intuitive and user-friendly navigation within your report. Using bookmarks, buttons, and links to enable users to move between different sections, pages, or drill-through levels.

Commentary and annotations: Add annotations, explanatory text, or commentary to provide context and explanations for the data presented. Using text boxes, titles, and captions to guide users and provide additional insights.

Dynamic filtering and slicers: Incorporating slicers or interactive filtering options to allow users to dynamically filter and explore the data.

Data storytelling: Using your report design to tell a compelling data story. Structuring your report in a narrative flow, highlighting key findings and insights along the way. Leveraging visuals, annotations, and narrative text to guide users through the story.

• Databases
• Excel files
• SharePoint
• Online services
• Cloud platforms

Introduction to the Query Editor interface:  Learn how to navigate the different tabs, preview data, and access various data transformation options.

Importing and loading data: Know how to import data into Power Query from different sources and load it into Power BI. You can choose to load the entire dataset or specify transformations before loading.

Data cleaning: Use Power Query's data cleaning capabilities to remove duplicates, filter rows, handle missing values, and apply data quality checks. This involves tasks like removing blank rows, replacing null values, and handling errors.

Column transformations: Perform various transformations on columns, such as renaming columns, changing data types, splitting columns based on delimiters, merging columns, and extracting specific parts of text.

Data shaping: Utilize shaping techniques like pivoting, unpivoting, and transposing data to reshape it according to your requirements. This involves reorganizing data between rows and columns.

Conditional transformations: Apply conditional logic to transform data based on specific criteria. This includes using IF statements, filtering data based on conditions, and creating custom conditional columns.

Merging and appending data: Combine data from multiple tables or data sources using merging and appending operations. Learn how to merge tables based on common columns or append tables vertically.

Grouping and aggregation: Group data based on specific criteria and perform aggregations such as sum, average, count, minimum, and maximum. Understand how to use the Group By and summarization functions in Power Query.

Custom columns and functions: Create custom columns using Power Query\'s formula language (M). Learn how to write custom functions to perform complex transformations and calculations on your data.

Parameterization: Parameterize queries to make them more flexible and reusable. This allows you to dynamically adjust values or filters within the query based on user input or external parameters.

Understand the different types of relationships: such as one-to-one, one-to-many, and many-to-many.

Cardinality and cross-filtering: Learn about cardinality, which defines the relationship between tables based on the number of unique values in a column. Understand how to set up cross-filtering behavior to control how filters flow between related tables.

Hierarchies: Define hierarchies within your data model to organize data into meaningful levels. Hierarchies are useful for drill-down analysis and enable users to navigate data at different levels of granularity easily.

Time intelligence: Learn how to incorporate time intelligence into your data model. Leveraging Power BI built-in functions and capabilities to handle time-based calculations such as year-to-date, quarter-to-date, or moving averages.

Data modeling best practices: Understand and implement data modeling best practices to optimize performance, reduce data redundancy, and ensure data accuracy. This includes techniques such as avoiding circular dependencies, minimizing calculated columns, and optimizing relationships.

Handling complex data scenarios: Be prepared to handle complex data scenarios such as snowflake schemas, slowly changing dimensions, or complex business logic requirements. Leveraging Power BI features and techniques to address these scenarios effectively.

Using perspectives: Create perspectives to organize and simplify the view of your data model. Perspectives allow users to focus on specific aspects of the data model, making it easier to navigate and work with.

Row-level security: Implement row-level security to control access to data based on user roles or permissions. This allows you to restrict data visibility and ensure data security within your data model.

Testing and validating the data model: Perform thorough testing and validation of your data model to ensure its accuracy and reliability. Verify that calculations, relationships, and hierarchies are working as expected.

Syntax and operators: Understand the syntax of DAX formulas, including operators (+, -, *, /), parentheses, and logical operators (AND, OR, NOT).

Calculated columns: Use DAX to create calculated columns within your tables. 

DAX Measures: Learn how to create Measures using DAX functions such as SUM, AVERAGE, COUNT, MAX, MIN, and more.

DAX functions: Gain familiarity with a variety of DAX functions available for various purposes. These include mathematical functions (e.g., ABS, SQRT), statistical functions (e.g., AVERAGEX, STDEV), time intelligence functions (e.g., SAMEPERIODLASTYEAR, DATESYTD), text functions (e.g., CONCATENATE, LEFT), and many more.

Contexts: Understand the concept of row context and filter context in DAX. 

Aggregation functions: Learn about DAX functions used for aggregations, such as SUMX, AVERAGEX, and COUNTX. These functions allow you to perform calculations across multiple rows and tables, applying filters and iterating through data.

Time intelligence functions: Leveraing Power BI time intelligence functions like TOTALYTD, PREVIOUSMONTH, and DATEADD for analyzing data over time.

Filtering and CALCULATE function: Learn how to use the CALCULATE function to modify the filter context and apply specific filters within a DAX expression.

Variables: Utilize variables to store intermediate results or expressions within DAX formulas.

Error handling: Implement error handling techniques like IFERROR, ISERROR, and BLANK in DAX to handle scenarios where calculations might result in errors. 

Iterating functions: Leveraging DAX iterating functions like SUMX, AVERAGEX, and MAXX to iterate over a table or a set of values and perform calculations for each iteration.

Advanced calculations: Explore advanced DAX concepts such as parent-child hierarchies, dynamic filtering using USERELATIONSHIP, ranking functions (RANKX, TOPN), and advanced time intelligence calculations (e.g., rolling averages, year-over-year growth).

Choosing the right chart types: Common chart types include bar charts, line charts, pie charts, scatter plots, area charts, and maps. Understand the strengths and limitations of each chart type to make informed choices.

Simplifying and declutter: Keep your visualizations clean and simple to avoid overwhelming the viewer. Minimize the use of unnecessary elements, such as excessive gridlines or labels. Emphasize the key information and remove distractions.

Providing context: Provide context and reference points to help viewers interpret the data accurately. Include axis labels, legends, and units of measurement. Use reference lines or benchmarks to compare data against a standard or target.

Interactivity: Leveraging interactive features in Power BI to enhance data exploration and analysis. Using tooltips, drill-through functionality, slicers, and filters to allow users to interact with the visualizations and dive deeper into the data.

Advanced visualizations: Exploring advanced visualizations like treemaps, heat maps, waterfall charts, box plots, or custom visualizations available through Power BI marketplace or development.