Power BI Bootcamp ( Zero to Hero) - Just 5 Hours

Extract and explore a financial dataset in power query, then apply data transformation techniques to analyze and understand the dataset as you start section two.

Import an Excel financial sample into Power BI, rename tables and columns, verify data types, and use choose columns and go to column to select the needed columns.

Learn how to remove columns in Power Query by choosing remove columns for the selected column or removing all other columns, with examples using country, segment, and product.

Learn to replace values in Power BI with Power Query Editor by duplicating a column and creating a country code, using match entire cell contents and advanced options.

Sort columns ascending or descending in Power Query editor to organize data. Keep or remove rows, top or bottom rows, remove duplicates, and handle errors or blanks.

Explore data transformation in Power BI by using transpose, count rows, rename, reverse rows, and other shaping techniques, with emphasis on feature locations and practical examples.

Explore Power BI's group by functionality, using basic and advanced options to aggregate sales by country, segment, product, and discount band, then format results for multi-level granularity.

Master formatting techniques in the transform ribbon: convert data to lowercase, uppercase, or proper case, trim and clean values, and add prefixes or suffixes to standardize fields.

Open Power BI desktop, transform data, merge country and segment as 'computer segment' using colon, comma, equals with spaces, then split by the leftmost delimiter.

Explore enter data to create self-contained Power BI tables, then apply transforms like transpose, group by, pivot/unpivot, and refresh workflows for live report development.

Learn to choose Power BI visuals using three principles, applying KPI and card visuals for emphasis, and column, line, and pie charts to communicate trends and insights.

Create a standard date table in Power BI using methods: Power Query M code and DAX calendar function, with start and end dates and fields like year, quarter, and month.

Create and format clustered bar chart and clustered column chart in Power BI, using data view and a sales measure to visualize product sales and refine axes, gridlines, and visuals.

Create and format pie, donut, and treemap visuals in Power BI, using a four‑category limit and percentage of total labels to clearly compare discount bands by sales.

Explore KPI visuals in Power BI, including card, gauge, multi-row card, and KPI visuals, to present revenue, total quantity, total orders, total cost, and profits with target comparisons and formatting.

Explore regular and field maps in Power BI, using locational data with or without latitude and longitude, adjusting bubble size, map styles, tooltips, legends, and interactive zoom.

Explore line, area, and stacked area charts in Power BI to visualize profits and sales by product or customer over time, using slicers and a date slicer for trend analysis.

Explore stacking visuals in Power BI, including 100% stacked bar and column charts, formatting axes, legend, and titles while analyzing country sales and discount bands.

Master line and stacked column charts and line and clustered column charts in Power BI, and format axes and legends while exploring country and product breakdowns with visuals from marketplace.

Explore funnel, ribbon, and waterfall charts in Power BI, transforming visuals to analyze country and product sales. Prepare for real-time data, data modeling, and DAX fundamentals.

Explore a case study to build a Power BI dashboard from a client dataset, applying data collection, transformation, modeling, and DAX to reveal sales, cost, quantity, and profit margin.

Connect to the Excel data source and transform datasets, renaming them to customers, locations, product, and salespeople. Review data types, such as text, decimal, and whole numbers, to prepare modelling.

Explore dimension and fact tables in data modeling. Learn how dimension tables hold unique records with descriptive data, while fact tables contain numeric data and ID columns.

Master the four cardinalities—one to many, many to one, one to one, and many to many—and convert many-to-many to many-to-one in a dimension–fact data model.

Create a date table and build a data model in Power BI Bootcamp by defining dimension tables, a fact table, and establishing relationships for insightful visuals.

Explore data analysis expressions (DAX) in Power BI, focusing on filter context and row context, and how aggregators, iterators, time intelligence functions, and other DAX functions fit together.

Explore aggregator functions in Power BI, including sum, count, min, and max, and how they work within filter context. Create a table and new measures to compute total quantity.

Master aggregator functions in Power BI by using count and count all to tally data elements. Count excludes nulls and blank rows, while count all includes them.

Discover how the average aggregator function computes the mean of values in the sales table, using total quantity and average quantity, alongside sum and count basics.

Learn the distinct count function to derive the unique number of values, illustrated by 12 unique locations from 97 states, with a sample measure.

Master min and max functions in Power BI to extract the minimum and maximum values from a dataset's cost column, and create measures like mincost and maxcost.

Discover the calculate specifier in dax to embed iterator and aggregator functions, enabling multiple statements and measures like total sales and average quantity for power bi analytics.

Compute total sales in Power BI using sumx, multiplying quantity by current price across related tables, and use the related function to fetch price from the products table.

Use countax to count rows in the locations table and tally counties in row context, an iterative measure built with calculate to apply filters and verify 97 counties.

Learn to compute average sales using the averagex iterator, creating a new measure with calculate, using row context and related tables to pull price and quantity.

Learn how to use countrows to calculate the total number of rows in a sales table, create a new measure, and verify results in transform data statistics count values.

Master MINX and MAXX iterator functions to compute the minimum and maximum values from a column, with flexible DAX expressions and cross-table references, demonstrated on the products tax column.

Discover how to use the DAX filter function in Power BI to calculate specific product sales with CALCULATE and FILTER, selecting by product name in the products table.

Discover the all function and its purpose in Power BI, removing context filters to reveal grand total sales. See how the divide function computes product-level percentages of total sales.

Explore year-to-date (YTD) functions in Power BI, calculating total sales from the year's start to today with TOTALYTD and DATESYTD, using a date table.

The lecture explains quarter-to-date functions, TOTALQTD() and DATESQTD(), to compute sales from the start of the current quarter to today, using two methods to build QTD measures.

master month-to-date analysis in power bi using datesmtd and totalmtd, creating mtd sales measures with a current-month date filter, and applying dateadd with same period last year.

Explore the dateadd function in Power BI to traverse time forwards or backwards by year, quarter, or month, and create measures such as two quarters ago using calculate.

Master the same period last year function to calculate total sales from the date table, creating a measure that returns last year sales in Power BI.

Build an end-to-end real-time Power BI report by applying DAX measures, data model, and transformations, and create theme-driven visuals, slicers, maps, and a two-page navigation using bookmarks.