Data Analysis and Visualization with Microsoft Power BI 2020

Learn how to import and ingest data for Power BI, comparing direct query, data import, and live connections, and choose approaches for data warehouses, data lakes, and various source systems.

Learn how to import CSV files, comma-separated values, into Power BI Desktop, including the steps to connect: get data, click files, locate a file, and load it.

Learn to import csv data into Power BI Desktop by using get data, connect to a csv file, view delimiter and source settings, load the data, and explore loaded tables.

Learn how to import data from Excel into Power BI Desktop, including saving workbooks as compatible Excel file types and connecting from OneDrive or SharePoint.

Learn to import data from an Excel file into Power BI Desktop by using getData, selecting Excel, navigating sheets, and loading a chosen table.

Import data from the web into Power BI Desktop using Get Data > Web, noting basic authentication limits. Connect to Wikipedia page, review tables, and select a table to visualize.

Learn how to import data from the web into Power BI Desktop by connecting to a web page, choosing HTML tables with the preview, and loading a table for visualizations.

Import real-time streaming data into Power BI to update dashboards in real time, using automatic page refresh or streaming datasets pushed via the REST API or streaming analytics.

Learn to import streaming real-time data into Power BI services by creating a streaming dataset via a rest API and configuring channels and fields such as radiation, humidity, and temperature.

Explore data cleaning and transformation with Power Query, using the M language to remove duplicates, handle missing values, and standardize data for analysis.

Learn Power Query basics for cleaning and shaping data in Power BI, including loading data, removing rows and columns, renaming, splitting, replacing values, and creating a sales per unit calculation.

Append queries stack two or more queries into one result set, using the same columns. It does not remove duplicates and creates null values when columns differ.

Explore how to load multiple data files, transform data, and add a custom state name column in Power BI, then append three queries into a single all states dataset.

Learn how merge queries in Power BI join two data queries by matching keys, producing a result set with selected columns, and explore the six join types.

Use merge queries in Power BI to join tables by zip code with a left outer join, load a CSV source, expand merged fields, and rename the manager column.

Explore Power BI visuals, including preinstalled visuals, and learn when to use horizontal bar charts, bar charts, column charts, and line charts to compare categories and track changes over time.

Explore stacked bar and stacked column charts in Power BI to break totals into subcategories with a second dimension and a measure, showing parts of the whole and time-based changes.

Learn to create bar and column charts in Power BI by importing Excel data, loading the financial sheet, and exploring stacked visuals that adapt as attributes are added.

Discover how line charts map continuous data over time, depicting closing prices and price action with a connected line, and use them to compare groups and identify trends and anomalies.

Create a line chart from the sales data by date, filter to a year, and drill down to quarters and months, adding cost of goods sold as a second line.

Discover how a pie chart visualizes a total divided among categories with radial slices, showing each category’s proportion and clear use guidelines, including a seven-category limit.

Learn to create a pie chart in Power BI 2020 using sales data by product category, adjust legends and data labels, enable tooltips for profit, and manage detail categories.

Build map charts in Power BI to visualize locations with interactive shapes and markers via Bing Maps geocoding. Add latitude and longitude to reduce ambiguity and use geo hierarchies.

Explore how to create and customize a map chart in Power BI Desktop, using country-level sales data, bubble sizes to show sales, and tooltips for discounts, with legends for product.

Learn to use cards and multitool cards in Power BI to visualize key metrics. Apply single-number cards for totals like sales or market share and group data with multi-card layouts.

Learn to use card and multi-row cards in Power BI to show total sales, gross sales, and country- and product-wise sales, with options for max or percent of grand total.

Discover key performance indicators (KPIs) as measurable values that quantify progress toward strategic objectives. Learn how KPIs at multiple levels guide decision making and assess performance across departments.

Learn to build KPI visuals in Power BI, set monthly targets like Target Units Sold, compare actuals to goals using CPI's, and visualize when you meet or miss targets.

Create word clouds visualizing text data, with word size indicating frequency or importance, enabling analysis of customer feedback and identifying what customers like most and pain points like wait time.

Import a custom word cloud visual into Power BI desktop, connect text data, adjust the delimiter to one column, and read word frequency from text size and counts.

Explore how Power BI uses a semantic model based on the tabular object model to connect data sources through relationships, enabling custom calculations and deterministic filter propagation.

Learn to model data in Power BI by loading four Excel queries, transforming and renaming fields, and establishing many-to-one relationships—both automatically detected and manually created—to enable reporting and visualization.

Learn data normalization and denormalization in Power BI, splitting repeated values into related tables and linking them with keys. See how denormalization supports reporting by combining delivery and customer data.

Explore OLTP and OLAP: OLTP processes many short transactions with fast queries and strict data integrity, while OLAP analyzes data across databases for business decisions and planning.

Explore the two main multidimensional schemas, star and snowflake, for data warehousing, including how fact tables and dimension and sub-dimension tables interact and trade-offs in space, maintenance, and query performance.

Learn DAX, the data analysis expressions language from Microsoft for Power BI, Power Pivot, and SSAS tabular models, with data types and arithmetic, comparison, text, and logical operators.

Create custom measures in Power BI 2020 by adding a measure named total sales and using the sum function on internet sales extended amount. Validate results across categories with visuals.

Create measures in Power BI using basic functions like average, max, and min on the fact internet sales extended amount, and adjust decimals for clear visuals by product category.

Create a measure that uses the same period last year with the time analysis function to compare sales by quarter in the date table, using calculate on new total sales.

Create a calendar date table for time analysis and time intelligence in Power BI using the calendar function, define min and max dates, and derive year, quarter, month, and day.

Power BI capstone project: import Excel data, transform it, build relationships, and create interactive visuals—branch maps, donut charts for manager sales, line charts for targets, and slicers for dynamic dashboards.