3.3.1 Intro to productionalizing your pipeline
Diving into the basic tenets of moving from development to production.
Building a Data Agency
How you can offer "data pipelines as a service" on Google BigQuery, following our end-to-end process
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Table of contents
Getting Started + FAQs
Getting Started + FAQs
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***ALL THE TEMPLATE LINKS***
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**GETTING HELP**
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The business of data, end-to-end
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Why'd we republish this course?
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Who is this for, and what will you learn?
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What is a data pipeline?
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[THROWBACK ALERT] WTF is ADP?
Additional (FREE) CIFL Courses
Additional (FREE) CIFL Courses
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Getting Started with BigQuery SQL
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Data Studio the Lazy Way
0.1 The Sales Flow
0.1 The Sales Flow
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0.1.1 Finding your niche
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0.1.2 Building an inbound content strategy
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0.1.3 Why we arrived at the sprint pricing model
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0.1.4 Why we publish pricing
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0.1.5 The initial sales call
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0.1.6 The roadmapping process
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0.1.7 Deal closing + contracts
0.2 Staffing & Resourcing
0.2 Staffing & Resourcing
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0.2.1 The sprint flow + roles
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0.2.2 Hiring reporting + data modeling analysts
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COMING SOON - Making a staffing plan & budget
1.1 Planning Development Sprints
1.1 Planning Development Sprints
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1.1.0 Meet the Tracking Plan
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1.1.1 Breaking the roadmap into a Tracking Plan
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1.1.2 Mapping our raw data source requirements
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1.1.3 What you'll do with data source schemas
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1.1.4 Mapping out data source schemas
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1.1.5 Populating key starter questions for reporting
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1.1.6 Scoping out each Site or Client
2.1 Data Feeds - Getting Started
2.1 Data Feeds - Getting Started
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2.1.1 Intro to data feeds
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2.1.2 BigQuery initial setup
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2.1.3 Setting up your BigQuery tables
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2.1.4 Pushing data from Sheets to BigQuery
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2.1.5 Supermetrics quickstart for beginners
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2.1.6 Pulling data from unsupported APIs into the Tracking Plan
2.2 Data Feeds - Stitch
2.2 Data Feeds - Stitch
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2.2.1 Stitch initial setup
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2.2.2 Pulling GA data using Stitch
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2.2.3 Pulling Adwords data using Stitch
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2.2.4 Pulling FB Ads data using Stitch
3.1 Intro to dbt
3.1 Intro to dbt
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3.1.1 Intro to dbt for SQL data modeling
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3.1.2 Planning your Data Models
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3.1.3 Creating your dbt project
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3.1.4 Connect your BigQuery database to dbt
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3.1.5 Managing your dbt project via Github
3.2 Data modeling with dbt
3.2 Data modeling with dbt
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3.2.1 Writing your 'processing' level SQL queries
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3.2.2 Writing your 'join' level SQL models
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3.2.3 Sidenote: on debugging dbt models
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3.2.4 Pro tip: standardizing URL structure
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3.2.5 Pro tip: using dbt macros
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3.2.6 Writing your 'admin' level SQL models
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3.2.7 Writing your 'math' and 'visualization' level SQL models
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COMING SOON - Data documentation in dbt
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COMING SOON - Data + schema testing in dbt
3.3 Productionalizing your dbt project
3.3 Productionalizing your dbt project
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3.3.1 Intro to productionalizing your pipeline
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3.3.2 Using dbt cloud to run your SQL models on a schedule
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3.3.3 Scheduling your data pipeline orchestrations
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3.3.4 Testing changes to your data pipeline
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3.3.5 QCing data using Supermetrics as a check
4.1 Visualizations in Data Studio
4.1 Visualizations in Data Studio
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4.1.1 The "PDA" reporting design framework
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4.1.2 Designing reports in the Tracking Plan
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4.1.3 Executing the reporting build
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4.1.4 Reviewing reporting
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4.1.5 Pulling data from BigQuery into Sheets
5.1 Sprint wrapup + review
5.1 Sprint wrapup + review
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5.1.1 Conditions for closing out a sprint
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5.1.2 Wiring up reporting with live data
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5.1.3 Sharing draft models + visualizations with clients
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5.1.4 Transitioning to support mode
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