Explore the input step as the starting point of a Tableau Prep flow, connecting to diverse sources, previewing data, and configuring sampling, header options, and unions.

Group data by dimensions and apply aggregate functions to numeric fields in Tableau Prep to reduce rows and compute metrics like total cases and total death by continent and year.

Tableau Prep join step combines data from two or more tables on a common field, enabling you to bring in related details and perform calculations using fields from multiple sources.

Use the union step in Tableau Prep to combine data from tables with the same structure into one dataset. Manually merge mismatched fields and extract year from a slash-separated column.

Reshape data with the pivot step in Tableau Prep, converting columns to rows (and rows to columns when needed) to support wide-to-long analyses and prepare clean year data.

Use the new rows step in Tableau Prep to fill gaps in time series data and expand data by converting date ranges into individual rows, using numeric or date fields.

Explore the Tableau Prep output step, where transformed data is saved to files or published to data sources, including Excel, CSV, Hyper, SQL Server, and Salesforce Data Cloud.

Explore the end-to-end data pipeline in Tableau Prep by building a flow with multiple outputs, publishing to Tableau Cloud, and connecting to Tableau Desktop to create up-to-date dashboards.

Authenticate to Google Drive data, clean and deduplicate 2020–2023 sales data, remove USD prefixes, convert to numbers, union years into a single sales table, and fill null order priority values.

Connect to the products data source, authenticate, and clean the table by extracting the category and creating calculated fields to map categories; compute sales as quantity times unit price.

Import and clean the shipping table in Tableau Prep, perform inner joins on shipping id with sales data, remove duplicates, and save the flow as a package.

Pivot the target sales table to year and sales, extract year from order date, aggregate actual sales by category and year, and join with target sales for comparison.

Learn to prepare the customer table in Tableau Prep by deduplicating, keeping the latest interaction, deriving city/state/country, building a proper full name, validating emails, and exporting invalids to Tableau Cloud.

Publish flow to tableau cloud, select project, and name it; schedule output steps to generate actual versus target data set, clean superstore data set, and invalid emails data set.

Publish the flow from Google Drive to Tableau Cloud, including three data sources, automate the ETL, then verify updates by connecting Tableau Desktop to published sources and publishing the workbook.

Open the Tableau Cloud dashboard, update sales and lead sources, and run the data flow to refresh outputs. Cloud dashboards auto-update and reflect changes after scheduled or manual runs.

Master data cleaning, transformation, and automation in Tableau Prep by building flows—from input to output—using clean, aggregate, union, pivot, and new rows, then publish to Tableau Cloud.