Meet the Tracking Plan
A walkthrough of the Tracking Plan you'll be using to build out your pipeline - soak in the layout and make it your own.
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Table of contents
Intro to the Course Pipeline Project
Intro to the Course Pipeline Project
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WTF is ADP?
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Copy the Tracking Plan Template
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Check out the Demo Pipeline Tracking Plan
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Check out the Demo Pipeline SQL Models on Github
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Check out the Demo Pipeline Data Studio dashboard
Start your Pipeline with a Question
Start your Pipeline with a Question
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Intro to question asking
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Demo questions for the CIFL pipeline
Translating your Question into a Tracking Plan
Translating your Question into a Tracking Plan
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Meet the Tracking Plan
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Mapping out your Data Sources
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Planning your Data Models
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Scoping out each Site or Client
Firing up your Data Feeds
Firing up your Data Feeds
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Intro to data feeds
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BigQuery initial setup
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Setting up your BigQuery tables
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Pushing data from Sheets to BigQuery
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Supermetrics quickstart for beginners
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Pulling data from unsupported APIs into the Tracking Plan
Using Stitch for Automated Data Feeding
Using Stitch for Automated Data Feeding
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Stitch initial setup
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Pulling GA data using Stitch
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Pulling Adwords data using Stitch
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Pulling FB Ads data using Stitch
Writing SQL queries to answer your questions
Writing SQL queries to answer your questions
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Intro to DBT for SQL data modeling
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Creating your DBT project
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Connect your BigQuery database to DBT
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Writing your 'processing' level SQL queries
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Writing your 'join' level SQL models
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Sidenote: on debugging DBT models
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Pro tip: standardizing URL structure
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Pro tip: using DBT macros
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Writing your 'admin' level SQL models
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Writing your 'math' and 'visualization' level SQL models
Visualizing your analysis in Data Studio
Visualizing your analysis in Data Studio
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Intro to visualization with Data Studio
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QCing your raw data in Data Studio
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Reaching the summit: answering your question
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Answering ancillary questions
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Pulling data from BigQuery into Sheets
Putting your Pipeline into production
Putting your Pipeline into production
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Intro to productionalizing your pipeline
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Pushing your SQL models to Github
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Using Sinter to run your SQL models on a schedule
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Scheduling your data pipeline
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Testing changes to your data pipeline
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QCing data using Supermetrics as a check
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