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AWS analytics

AWS data analytics: from S3 to dashboards

We design analytics on AWS using the services that fit your scale, from a simple S3 and Athena set-up to Redshift, Glue and streaming pipelines.

Talk to our teamBook a discovery call
  • S3 data lakes with Glue and Athena
  • Amazon Redshift warehouses
  • Kinesis and MSK streaming
  • QuickSight, Power BI or Tableau on top

AWS analytics services

Architecture

Account structure, storage layout and service choices documented.

ETL

Glue jobs, Step Functions or dbt for transformation.

Warehousing

Redshift design, workload management and tuning.

Security

Lake Formation permissions, encryption and audit logging.

How an analytics engagement runs

  1. Step 1

    Questions first

    We agree the decisions the data should support and the measures that matter.

  2. Step 2

    Data review

    We profile your sources, note quality issues and confirm what is feasible.

  3. Step 3

    Build in slices

    Pipelines, models and reports are delivered one subject area at a time.

  4. Step 4

    Hand over

    Documentation, access controls and training so your team can run and extend it.

Frequently asked questions

Athena or Redshift?

Athena suits ad hoc queries on lake data; Redshift suits heavy, repeated BI workloads. Many teams use both.

Can you work with the tools we already pay for?

Yes. We usually build on your existing cloud, warehouse and BI licences, and recommend new tools only when there is a clear gap.

Related services

Tell us what you are working on

Share your goals and current setup. We will come back with questions, a suggested approach and the next steps.

Contact Raushang4 Technology