Excel Power Query, Power Pivot, DAX, Power BI & Power 3D Map

Import csv files, use the power query editor to clean and delete unwanted data, load it into a worksheet, apply filters, and learn to unpivot and pivot data.

Define what a csv file is and how comma separated values work, with headers and delimiters. Show how Power Query transforms csv data into an analysis-friendly layout in Excel.

Normalize data by ensuring every attribute has its own column, enabling robust storage and analysis, reducing storage, easing maintenance, and speeding queries.

Import a csv file using power query, remove header rows, and transform data so dates appear in one column, creating a clean sales list with step-by-step data shaping.

Learn to shape a data table in Power Query Editor by renaming, reordering, deleting columns, and merging two columns to create a single Make and Model field.

Discover row-based data shaping in Power Query, using keep and remove techniques, sampling methods, and handling duplicates. Learn to sort, group, and reverse rows to tailor data for analysis.

Set the correct data types early to ensure accurate calculations and slicing, using Power Query's auto detect where possible and manually adjusting with the data type tool when needed.

Replace values across a column to standardize data and correct entries in Power Query, using the replace values dialog and advanced options, with text conversion for non-text columns as needed.

Explore how Power Query transforms column contents with text formatting, numeric rounding, and date-time extractions. Learn practical steps to uppercase text, trim spaces, round numbers, and extract year from dates.

Explore data mashup with Power Query to extend datasets via derived columns, joins, and pivoting, delivering a standardized, usable data model. Manage queries with the view and advanced editor ribbons.

Discover how to split columns in Power Query by delimiter or fixed characters, including custom delimiters, to separate dates, numbers, or text elements.

Add an index column to number records, starting at zero or a custom start, and use it as a surrogate key for dimensional modeling and to reapply sort orders.

Pivot and unpivot data inside Power Query to cleanse and transform datasets, transforming rows and columns for efficient data loading and reporting, including append and flatten operations.

Learn to handle multiple date formats and invalid dates with Power Query, set the English United States locale, and transform data to correct date time values.

Learn how to use column from examples in Power Query to create new columns from sample values, reveal transformations, and bucket numeric sizes into XL, L, M, S for analytics.

Unify data from multiple sources into tables, join queries, and build an ETL workflow in Excel using Power Query, Power Pivot, DAX, Power BI, and Power 3D Map.

Explore Power Query to pull, transform, and refresh data from Excel workbooks, external files, databases, and folders; learn appending, merging, unpivoting, pivoting, and basic M language to streamline your analysis.

Learn to use Power Query to split a column by a delimiter, transform data from a workbook, rename steps, and load results to a worksheet with refresh tips.

Apply a range of transformations in power query to clean and shape HR course evaluation data, including removing rows, promoting headers, filtering nulls, and deduplicating.

Discover how to unpivot data in Power Query, troubleshoot common query errors, and transform pivoted data back to a flattened form using unpivot other columns and M code edits.

Learn to merge category and color lookups into the product query using Power Query Editor, performing left outer joins and expanding results for a data model and pivot table.

Load categories, colors, and products as separate tables into the data model, establish one-to-many relationships, and hide key codes to streamline pivot tables and visuals.

Transform a messy invoice dataset with Power Query by splitting a single expenses cell into rows, then group by invoice to compute total expenses and refresh results.

Fuse power query and power pivot to stage data from diverse sources into a dynamic data model. Create relationships and KPI calculations for code-free analysis in Excel.

Load data into the Power Pivot data model using Power Query or direct import, connect to databases, create a calendar table, and build relationships for analysis.

Explore how database normalization separates facts from attributes using a sales fact table and product and data dimension tables to ensure integrity, and relate to Power Query and DAX workflows.

Learn how DAX powers Power BI and Power Pivot with calculated columns and measures. Discover row context versus filter context and DAX differs from Excel formulas in building dynamic visuals.

Create a calculated column direct costs in the stock table by adding purchase price and related costs, including parts and labor, with Excel-like arithmetic applied to every row.

Leverage DAX to build complex if statements using and/or across related tables, as shown by flagging red or blue coupes and creating a special sales column.

Create and link a slicer to a pivot table in PowerPivot, filter by country, test the slicer, link it to pivot tables, and save the workbook.