Master big data analytics on AWS with Kinesis for real-time streaming, Glue and EMR for data processing, Athena and Redshift for analytics, and QuickSight for visualization.
AWS Data Analytics Specialists design and implement big data analytics solutions on AWS. You'll build data lakes with S3 and Lake Formation, process streaming data with Kinesis, transform data using Glue and EMR, query data with Athena, build data warehouses with Redshift, and create visualizations with QuickSight to drive business insights.
Solutions Architect Associate
Recommended FoundationData Analytics Specialty
After Phase 6The AWS Certified Data Analytics - Specialty (DAS-C01) exam tests your knowledge across six key domains:
If you're new to AWS Data Analytics:
→Begin with Phase 1: Data Collection & Ingestion (expand below)
→Complete AWS Solutions Architect Associate first if you lack AWS fundamentals
→Kinesis, Glue, Athena, and Redshift are critical - they're 60% of the exam
→Focus on one phase at a time — finish it completely before moving forward
Already have data analytics experience?
→Jump to the phase that matches your current skill level
Shards, partition keys, enhanced fan-out, retention (24h-365d), on-demand vs provisioned mode
Managed delivery to S3/Redshift/Elasticsearch, buffering, transformations, format conversion (JSON→Parquet/ORC), dynamic partitioning
SQL queries on streaming data, windowing (tumbling/sliding/session), aggregations, real-time processing
Device connectivity (MQTT/HTTPS), device shadows, rules engine, integration with Kinesis/S3/Lambda
Kinesis represents ~20% of the DAS-C01 exam. Master all three Kinesis services and understand when to use each. Real-time streaming is critical for analytics workloads.
Storage classes, lifecycle policies, partitioning strategies, S3 Select, Object Lock, versioning
Centralized data lake, ingestion blueprints, fine-grained access control, integration with Glue Catalog
Central metadata repository, crawlers, database/table definitions, integration with Athena/Redshift Spectrum/EMR
S3 and Lake Formation represent ~15% of the exam. Understand partitioning strategies, storage classes, and how Lake Formation simplifies data lake security.
Spark-based ETL jobs, visual ETL editor, job bookmarks, triggers, dynamic frames, pushdown predicates, DataBrew
Hadoop, Spark, Hive, Presto, Flink, cluster architecture (master/core/task nodes), transient vs long-running, Spot instances, EMRFS
Serverless data processing, event-driven (S3/Kinesis/DynamoDB Streams), lightweight transformations
Glue and EMR represent ~35% combined. Master ETL job design, understand when to use Glue vs EMR, and optimize for cost with Spot instances.
Serverless SQL on S3, Presto engine, partitioning, columnar formats (Parquet/ORC), compression, workgroups, federated queries
Columnar MPP data warehouse, distribution styles (KEY/ALL/EVEN), sort keys, VACUUM/ANALYZE, Concurrency Scaling, Spectrum, Materialized Views
Athena and Redshift represent ~35% combined. Master Athena optimization (partitioning, columnar formats) and Redshift design (distribution keys, sort keys).
Serverless BI, SPICE in-memory engine, ML Insights (anomaly detection, forecasting), dashboards, embedded analytics, row/column-level security
QuickSight represents ~10% of the exam. Understand SPICE, data source connections, and security features.
KMS encryption (at rest), TLS/SSL (in transit), VPC configuration, IAM policies, Lake Formation permissions, Macie for PII discovery
S3 Intelligent-Tiering, EMR Spot instances, Athena optimization (partitioning, compression, columnar), Redshift pause/resume, Reserved capacity
Complete 3-4 full practice exams, review scenarios, master service trade-offs, focus on Kinesis/Glue/Athena/Redshift
DAS-C01: AWS Certified Data Analytics - Specialty
This certification validates your expertise in designing and implementing AWS data analytics solutions. Exam details: 180 minutes, 65 questions, $300 USD, passing score 750/1000.
Practice DAS-C01 QuestionsDesign real-time analytics with Kinesis Data Streams, Analytics, and Firehose
Build S3 data lakes with Lake Formation, implement partitioning strategies, configure access control
Design ETL pipelines with Glue, run Spark jobs on EMR, optimize for cost with Spot instances
Optimize Athena queries, design Redshift warehouses, build QuickSight dashboards
Implement encryption, configure Lake Formation permissions, ensure compliance
Validate your data analytics expertise with AWS's official Data Analytics Specialty credential