Data cleaning in Excel

Power Query enables data cleaning in Excel by performing ETL—extract, transform, and load data from CSV files or workbooks, then clean, transform, and load into pivot tables or tables.

Learn to access Power Query, load data from an Excel workbook and CSV files, refresh and load, and use Home, Transform, Column, and View ribbons to clean data.

Learn to replace values in Power Query with case-sensitive matching, view the original data, and use merge, append, pivot, split, and add column features to build a master sheet.

Master Power Query operations for cleaning data in Excel, including sorting, filtering with equals and contains, replacing nulls, transforming case, removing duplicates, and loading the final data for presentation.

Learn how data quality drives data warehouse testing, covering completeness, consistency, conformity, accuracy, and integrity, plus etl basics—extract, transform, load—from multiple sources.

Apply data transformation with Power Query to reshape data from csv file, apply filters, review columns, and load results into Excel; use Power BI for datasets over 1 million records.

Apply power theory to specify data types in excel, converting columns to string, number, or date formats, and define fields like name, id, birthday, children, and fee for clean data.

Learn to create a custom column in Power Query to concatenate first and last names into a full name, transform data, and load results into Excel.

Apply a custom if condition in Excel using Power Query to filter candidates by portfolio score and package score, decide interview or reject, and load results to CSV or cloud.

Master data cleaning in Excel by filling below null values in a column with Power Query, propagating the first row's value downward. Load the cleaned data and explore formatting options.

Learn to split a one-column dataset into id, name, age, and email columns using custom delimiters in Excel by splitting the column and renaming the results.

Learn to append and concatenate data from multiple sheets into a single master sheet with Power Query, refresh, and load the combined data for customer requirements.

Perform hands-on data cleaning in Excel through assignments, converting data to tables, setting data types, filling missing values, splitting by delimiter, and building conditional and concatenated columns with Power Query.

Explore cleaning data in Excel by turning data into tables, applying filters and conditional formatting, and perform descriptive analysis using the Data Analysis Toolpak to compute mean, median, and skewness.

Explore data categories such as transactional data, master data, reference data, and metadata, and understand how data quality, lineage, and governance create a single truth across systems, with currency codes.

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