Sisifo Analytics implements Databricks for companies that need one platform for their data, analytics and AI. We set up the lakehouse, build the pipelines, migrate legacy data and deliver the dashboards and models your teams use every day. Our team works with clients across Latin America, the United States and Europe from our base in Miami.
What does Sisifo do on Databricks?
We cover a Databricks project from architecture to adoption, so you work with one team instead of several vendors.
- Lakehouse architecture and setup: workspace design, environments, security and cost controls from day one.
- Data pipelines: ingestion from ERPs, CRMs, databases and files into Databricks, with automated, monitored jobs.
- Migration: moving on-premise databases and legacy data warehouses to Databricks without losing history.
- Data governance: access, lineage and data quality rules managed in Unity Catalog.
- Dashboards: Power BI and other BI tools connected to trusted Databricks tables.
- Data science and AI: machine learning models and AI agents built on the same governed data.

How does a Databricks project with Sisifo work?
We start with the foundation and add capabilities in order, so each step builds on reliable data.
- Assess: review your current data sources, tools and infrastructure.
- Build the foundation: set up the lakehouse and the data pipelines that feed it.
- Deliver visibility: connect business intelligence dashboards for daily decisions.
- Add advanced analytics: build data science models and AI tools on top of the platform.
- Drive adoption: train your teams and manage the change so the platform gets used.
Why work with Sisifo on Databricks?
Sisifo has delivered 50+ data projects across 10+ industries, with 18+ years of combined experience on the team. We are a Miami-based company with data and AI specialists from Latin America, and a Microsoft Solutions Partner for teams running Azure Databricks.
“Excellent experience working with Sísifo. They implemented our Data Warehouse and dashboards with great professionalism, clear communication, and strong follow-up throughout the project. A very reliable partner for data analytics and BI initiatives.”
Andres Finol, CEO

Which cloud should run your Databricks platform?
Databricks runs on Microsoft Azure, AWS and Google Cloud. We recommend the cloud based on where your data and systems live today, so you avoid extra transfer costs and duplicate contracts. See our work on Azure, AWS and Google Cloud, or compare Databricks with Snowflake.
Frequently asked questions

What does a Databricks implementation include?
A Databricks implementation includes the lakehouse setup, the pipelines that load your data, governance rules and the first dashboards or models your teams need. We define the exact scope after reviewing your current data sources and goals.
Can you migrate our existing data warehouse to Databricks?
Yes. We migrate on-premise databases and legacy data warehouses to Databricks, including historical data and the reports that depend on it. The migration runs in stages so your teams keep working while it happens.
Should we run Databricks on Azure, AWS or Google Cloud?
It depends on where your data and applications already live. Running Databricks on the same cloud avoids data transfer costs and keeps security in one place. We help you choose during the assessment.
Do you work with companies in Latin America?
Yes. Sisifo works with companies in Latin America, the United States and Europe. Our headquarters are in Miami and our team of data and AI specialists is from Latin America.
Can Power BI connect to Databricks?
Yes. Power BI connects directly to Databricks, so dashboards read from the same governed tables your analysts and models use. We build and automate those dashboards as part of the project.
How do we start a Databricks project with Sisifo?
Book a meeting with our team to walk through your data, tools and goals. From there we recommend where to begin, usually with an assessment of your current infrastructure.
Ready to build your Databricks platform?
Tell us where your data lives today and what you need from it.

