Cloud Technology and Services · Topic 9 of 11
AWS Analytics Services
Learn the AWS analytics services for CLF-C02: Athena, Glue, EMR, Kinesis, Redshift, QuickSight, OpenSearch Service, Lake Formation and MSK, by job.
- 4 min
- Athena queries data in S3 with SQL, serverless.
- Glue does ETL and keeps a data catalog.
- EMR runs big data frameworks such as Spark and Hadoop.
What it is
Analytics means turning raw data into useful answers. AWS provides services to collect data, store it, prepare it, query it and show the results.
A data lake is a central store of data in its original form, often built on Amazon Simple Storage Service (S3). A data warehouse is a database designed for fast analysis of large amounts of structured data.
The exam expects you to match each service to its step in this journey.
How it works
Querying and processing data
| Service | What it does | Choose it when |
|---|---|---|
| Amazon Athena | Runs Structured Query Language (SQL) queries directly on data in S3, with no servers to manage | You want quick ad hoc queries on files in S3 and pay per query |
| Amazon EMR | Managed big data clusters running frameworks such as Apache Spark and Hadoop | You need large scale data processing with open source tools |
| Amazon Redshift | Data warehouse for complex SQL analysis on large structured data | You need fast reporting over very large data sets |
| Amazon OpenSearch Service | Search and analysis of logs and text | You need log analytics or full text search |
Athena is serverless. You point it at data in S3, write SQL and read the result. Redshift keeps data in its own warehouse for heavy, repeated analysis.
Preparing and cataloguing data
AWS Glue is a serverless data integration service. It does extract, transform and load (ETL), which means reading data from sources, reshaping it and writing it to a target. It also keeps a data catalog that describes your data.
AWS Lake Formation helps you build and secure a data lake, including setting who can see which data.
Streaming data
Streaming data arrives continuously, such as clicks, sensor readings or logs. Services that handle it include:
| Service | Use |
|---|---|
| Amazon Kinesis Data Streams | Collect and process real time data streams |
| Amazon Data Firehose | Load streaming data into destinations such as S3 or Redshift |
| Amazon Managed Streaming for Apache Kafka (MSK) | Managed Apache Kafka for teams that use Kafka |
Choose Kinesis when you want an AWS native streaming service and MSK when you already use Kafka.
Visualising data
Amazon QuickSight is a business intelligence (BI) service. It creates dashboards and charts from data in sources such as S3, Athena and Redshift, and can be shared with users.
Data sharing and discovery
AWS Data Exchange lets you find and use third party data sets in AWS. It is useful when a company wants to buy or subscribe to outside data.
Putting it together
A typical flow starts with data arriving through Kinesis, landing in S3, being cleaned by Glue, queried by Athena, and shown in QuickSight. The point is not to memorise a pipeline but to know the one job of each service.
Data lake versus data warehouse
| Feature | Data lake | Data warehouse |
|---|---|---|
| Data | Any form, raw | Structured, prepared |
| Typical AWS service | S3 with Lake Formation | Redshift |
| Best for | Flexible exploration | Fast, repeatable reports |
What to remember for the exam
- Athena queries data in S3 with SQL, serverless.
- Glue does ETL and keeps a data catalog.
- EMR runs big data frameworks such as Spark and Hadoop.
- Redshift is the data warehouse for large scale SQL analytics.
- Kinesis processes real time streams, and Firehose delivers streams to stores. MSK is managed Kafka.
- QuickSight builds dashboards and visualisations.
- OpenSearch Service handles search and log analytics.
- Lake Formation builds and secures data lakes.
"Query files in S3 with SQL and no servers" means Athena. "Dashboards" means QuickSight. "Real time stream" means Kinesis.
Common mistakes
Confusing Athena and Redshift. Athena queries data in place in S3. Redshift loads data into a warehouse for repeated heavy analysis.
Choosing EMR for a simple query. EMR is for large scale processing with open source frameworks, while Athena is simpler.
Mixing up Glue and Lake Formation. Glue moves and prepares data. Lake Formation governs and organises a data lake.
Forgetting streaming services. If data arrives continuously, think Kinesis or MSK, not batch tools.
QuickSight shows data but does not store or prepare it. It sits at the end of the pipeline.
Check yourself
Which service runs SQL queries on files in S3 without servers?
Amazon Athena.
Which service creates business dashboards from data?
Amazon QuickSight.
Which service performs extract, transform and load jobs?
AWS Glue.
Topic 9 of 11 in Cloud Technology and Services
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