Sisifo Analytics designs and runs data platforms on Amazon Web Services for companies that already keep their applications on AWS. We organize raw data in Amazon S3, automate its processing, model it for analysis and connect it to the dashboards and AI tools your teams need. Clients in Latin America, the United States and Europe work with our Miami-based company and its team of specialists from Latin America.
How does Sisifo help companies on AWS?
AWS offers dozens of data services. Our job is to choose the few that fit your case and make them work together.
- Data lake on Amazon S3: a structured landing zone for raw, cleaned and curated data, with lifecycle rules that keep storage costs low.
- ETL with AWS Glue: jobs and crawlers that extract data from your ERP, CRM and databases, transform it and catalog it automatically.
- Amazon Redshift warehouse: dimensional models built for fast queries on sales, finance and operations data.
- Serverless queries: Amazon Athena for ad hoc analysis directly over the data lake, with no servers to manage.
- Dashboards: Power BI or Amazon QuickSight reports connected to curated AWS data.
- Machine learning and generative AI: models in Amazon SageMaker and AI assistants built on Amazon Bedrock.
What does an AWS data engagement look like?
We start small, prove value on one use case and then extend the platform to the rest of the business.
- Review: audit your AWS account, data sources and current reporting.
- Blueprint: draw the target architecture, security model and cost estimate.
- First use case: build the pipelines and dashboard for one priority area, such as sales or inventory.
- Scale out: add sources, business areas and users on the same foundation.
- Operate: monitor jobs, tune costs and hand over runbooks to your team.
What makes Sisifo a good fit for AWS projects?
Our team holds the AWS Certified Solutions Architect certification, so designs follow AWS guidance on security, reliability and cost from the start. Sisifo has completed 50+ projects across more than 10 industries, with 18+ years of combined experience and engineers across Latin America working from our Miami base.
“We had a great experience working with Sisifo Analytics. Their team helped us organize and structure our data across the Group in the Dominican Republic, and the dashboards they built gave us clear, actionable visibility into our operations. They are extremely responsive, well organized, and very efficient throughout the entire process. Communication was smooth, timelines were respected, and they truly understood our needs from both a business and analytical perspective.”
Jose Bonetti, Manager
Is AWS the right home for your data?
AWS is a strong choice when your applications, e-commerce or product data already run there, since moving data out of AWS adds cost and complexity. Teams standardized on Microsoft tools often do better on Azure, and analytics-first teams may prefer Google Cloud. You can also run Snowflake or Databricks on top of AWS.
Frequently asked questions
Which AWS services do you use for data projects?
Most projects combine Amazon S3, AWS Glue and Amazon Redshift or Athena, with Power BI or QuickSight for reporting. For AI we add Amazon SageMaker or Amazon Bedrock. We only add the services your use case needs.
Should we use Amazon Redshift or a data lake with Athena?
Redshift suits frequent, complex reporting with many users. Athena over an S3 data lake suits occasional queries on large volumes of raw data, since you pay per query. A common path is to start with Athena and add Redshift as reporting grows.
Can Power BI connect to data on AWS?
Yes. Power BI connects to Amazon Redshift and Athena, so you can keep your existing reports while the data moves to AWS. If you prefer to stay inside AWS, Amazon QuickSight is also an option.
Do you have AWS certified engineers?
Yes. Our team holds the AWS Certified Solutions Architect certification, which covers secure, reliable and cost-efficient design on AWS.
How do you control AWS data costs?
We use S3 storage tiers and lifecycle rules, pause or schedule compute when it is not needed and set AWS Budgets alerts. Cost reviews are part of the operate phase.
How do we begin an AWS data project with Sisifo?
Book a meeting and tell us which AWS services you already use and where your data comes from. We will suggest a first use case that shows results quickly.
Put your AWS data to work
Tell us what runs on AWS today and which questions your data should answer.
