2.2.2 Pulling GA data using Stitch

2.2.2 Pulling GA data using Stitch

Setting up your first GA feed with Stitch.  

See specific step-by-step instructions here - your metrics or dimensions may differ depending on your pipeline setup:

Building a Data Agency

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Getting Started + FAQs

  • ***ALL THE TEMPLATE LINKS***
  • **GETTING HELP**
  • The business of data, end-to-end
  • Why'd we republish this course?
  • Who is this for, and what will you learn?
  • What is a data pipeline?
  • [THROWBACK ALERT] WTF is ADP?

Additional (FREE) CIFL Courses

  • Getting Started with BigQuery SQL
  • Data Studio the Lazy Way

0.1 The Sales Flow

  • 0.1.1 Finding your niche
  • 0.1.2 Building an inbound content strategy
  • 0.1.3 Why we arrived at the sprint pricing model
  • 0.1.4 Why we publish pricing
  • 0.1.5 The initial sales call1
  • 0.1.6 The roadmapping process1
  • 0.1.7 Deal closing + contracts

0.2 Staffing & Resourcing

  • 0.2.1 The sprint flow + roles
  • 0.2.2 Hiring reporting + data modeling analysts
  • COMING SOON - Making a staffing plan & budget

1.1 Planning Development Sprints

  • 1.1.0 Meet the Tracking Plan
  • 1.1.1 Breaking the roadmap into a Tracking Plan
  • 1.1.2 Mapping our raw data source requirements
  • 1.1.3 What you'll do with data source schemas
  • 1.1.4 Mapping out data source schemas
  • 1.1.5 Populating key starter questions for reporting
  • 1.1.6 Scoping out each Site or Client

2.1 Data Feeds - Getting Started

  • 2.1.1 Intro to data feeds
  • 2.1.2 BigQuery initial setup
  • 2.1.3 Setting up your BigQuery tables
  • 2.1.4 Pushing data from Sheets to BigQuery
  • 2.1.5 Supermetrics quickstart for beginners
  • 2.1.6 Pulling data from unsupported APIs into the Tracking Plan

2.2 Data Feeds - Stitch

  • 2.2.1 Stitch initial setup
  • 2.2.2 Pulling GA data using Stitch
  • 2.2.3 Pulling Adwords data using Stitch
  • 2.2.4 Pulling FB Ads data using Stitch

3.1 Intro to dbt

  • 3.1.1 Intro to dbt for SQL data modeling
  • 3.1.2 Planning your Data Models
  • 3.1.3 Creating your dbt project
  • 3.1.4 Connect your BigQuery database to dbt
  • 3.1.5 Managing your dbt project via Github

3.2 Data modeling with dbt

  • 3.2.1 Writing your 'processing' level SQL queries
  • 3.2.2 Writing your 'join' level SQL models
  • 3.2.3 Sidenote: on debugging dbt models
  • 3.2.4 Pro tip: standardizing URL structure
  • 3.2.5 Pro tip: using dbt macros
  • 3.2.6 Writing your 'admin' level SQL models
  • 3.2.7 Writing your 'math' and 'visualization' level SQL models
  • COMING SOON - Data documentation in dbt
  • COMING SOON - Data + schema testing in dbt

3.3 Productionalizing your dbt project

  • 3.3.1 Intro to productionalizing your pipeline
  • 3.3.2 Using dbt cloud to run your SQL models on a schedule
  • 3.3.3 Scheduling your data pipeline orchestrations
  • 3.3.4 Testing changes to your data pipeline
  • 3.3.5 QCing data using Supermetrics as a check

4.1 Visualizations in Data Studio

  • 4.1.1 The "PDA" reporting design framework
  • 4.1.2 Designing reports in the Tracking Plan
  • 4.1.3 Executing the reporting build
  • 4.1.4 Reviewing reporting
  • 4.1.5 Pulling data from BigQuery into Sheets

5.1 Sprint wrapup + review

  • 5.1.1 Conditions for closing out a sprint
  • 5.1.2 Wiring up reporting with live data
  • 5.1.3 Sharing draft models + visualizations with clients
  • 5.1.4 Transitioning to support mode

Congrats!

  • Wapow! You made it.
  • Interested in working with CIFL?