ADP syllabus: every exam domain and topic

Data preparation and ingestion

30%

Getting data ready and into the right storage: transformation patterns, quality, transfer and load tools, formats and storage choices. About 30% of the exam.

Prepare and process data

Tell ETL, ELT and ETLT apart and say when each one fits
Pick a transfer tool for the job: Storage Transfer Service for online copies, Transfer Appliance for very large offline moves
Assess data quality: completeness, validity, consistency, uniqueness and timeliness
Clean data with BigQuery SQL, Cloud Data Fusion or Dataflow: duplicates, nulls, types and formats

File formats and data types

Recognise CSV, JSON, Avro, Parquet and relational tables, and what each costs or saves when loaded
Classify a use case as structured, semi-structured or unstructured data

Extraction and loading tools

Choose between Dataflow, BigQuery Data Transfer Service, Database Migration Service, Datastream and Cloud Data Fusion
Load data with gcloud storage, the bq command, Storage Transfer Service, BigQuery Data Transfer Service or client libraries

Choosing storage

Match Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable and Spanner to workloads
Pick a location type: zonal, regional, dual-region or multi-region

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Data analysis and presentation

27%

Finding answers in data with SQL and notebooks, presenting them in Looker, and building models with BigQuery ML. About 27% of the exam.

Data pipeline orchestration

18%

Choosing transformation and orchestration tools, scheduling and monitoring simple pipelines, and reacting to events. About 18% of the exam.

Designing simple pipelines

Select Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer or Dataform from the business need
Weigh ELT against ETL for a given scenario
Pick the products that make up a basic transformation pipeline

Scheduling and automation

Create and manage scheduled queries, Cloud Scheduler jobs and Cloud Composer schedules
Choose an orchestrator: Composer, scheduled queries, Dataproc Workflow Templates or Workflows

Monitoring

Follow a Dataflow pipeline in the job UI
Read logs and metrics in Cloud Logging and Cloud Monitoring

Event-driven pipelines

Identify when to stream from Pub/Sub into BigQuery
Use Eventarc triggers with Dataform, Dataflow, Cloud Run functions, Cloud Run and Cloud Composer

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Data management

25%

Controlling who can access data, how long it is kept, how it survives failures and how it is encrypted. About 25% of the exam.