Welcome to our FAQ page! Here, you will be able to find the most frequently asked questions about Gemma Analytics.

👋General

What services do you provide?

In short, Gemma Analytics provides analytics as a service. In order to do this, we offer the following sub-products:

• Data Engineering
  • e.g. setting up a data infrastructure DevOps & DataOps
  • e.g. setting up data pipelines → connecting to raw sources and moving from them (ETL/ELT) and to them (reverse ETL/ELT)
• Analytics Engineering
  • e.g. transformation of raw data sets into tested, connected data sets that then get consumed by a visualization tool, a data science use case, or by another production system
• Data Analysis
  • e.g. visualization, ad-hoc analyses, documentation, workshops for clients
• Data Leadership
  • e.g. KPI setting, strategy building, and hiring of data teams

How do you finance yourself?

Gemma is a profitable company, meaning that we do not rely on funding from banks or VCs. While this is partly due to the fact that we prefer to stay independent, it is also true that we do not believe that a service company like ours should follow a VC model.

Some of our team enjoying one of our monthly team dinners. ****

During the company offsite in Zillertal, Austria.

💻Tech stack

What does your tech stack look like?

In general, we implement in the existing structure of the client (if applicable), yet have opinions and preferences on what tools we recommend and aim to work with. If we need to design a new data infrastructure, this is what we advise to work with:

• Data Loading
  • For the majority of clients, we use Apache Airflow and use our own open-source Python library EWAH
  • For simple requests, we work with Fivetran or Stitch or Airbyte
• Data Warehousing
  • For smaller data loads, we mostly use PostgreSQL databases
  • For larger datasets, we work with Snowflake or BigQuery