About Yaetos-Labs

Yaetos provides an open-source data framework that simplifies the creation of data pipelines for business intelligence and artificial intelligence applications, enabling users to process and analyze data without extensive programming knowledge. The platform eliminates data silos and accelerates access to trusted insights, allowing teams to implement effective data solutions in days rather than months.

```xml <problem> Creating and managing data pipelines for business intelligence (BI) and artificial intelligence (AI) applications can be complex and time-consuming, often requiring extensive programming knowledge and specialized skills. This complexity can hinder organizations from efficiently processing and analyzing data, leading to delays in accessing valuable insights. </problem> <solution> Yaetos offers an open-source data framework designed to simplify the creation of data pipelines for BI and AI. The framework allows data engineers, scientists, and analysts to focus on business growth by streamlining the data pipeline process. It integrates a suite of modern data and analytics tools within a cloud environment, enabling users to build a "data engine" without needing in-depth programming expertise. Yaetos promotes modern development practices like CI/CD and GitOps, integrating open-source tools such as Pandas and Spark. </solution> <features> - Simplifies data pipeline creation with minimal programming knowledge, while providing access to the full Python environment for advanced users. - Integrates with open-source tools like Pandas and Spark for data transformation. - Supports modern development practices such as CI/CD and GitOps. - Designed for cost efficiency by encouraging the use of a data lake and utilizing resources billed only for computation time. - Can extract data from various sources, including databases, REST APIs, and SaaS services (e.g., Salesforce, Stripe). - Supports data transformations in SQL or Python. - Compatible with small, normal, and big data volumes. </features> <target_audience> The primary users are data engineers, data scientists, and analysts across various industries who need to build and manage data pipelines for BI and AI applications. </target_audience> ```

What does Yaetos-Labs do?

Where is Yaetos-Labs located?

Yaetos-Labs is based in Barcelona, Spain.

When was Yaetos-Labs founded?

Yaetos-Labs was founded in 2024.

Location

Barcelona, Spain

Founded

2024

Employees

5 employees

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Yaetos-Labs

Score: 59/100

AI-Generated Company Overview (experimental) – could contain errors

Executive Summary

yaetos.com 100+

Founded 2024 – Barcelona, Spain

Funding

No funding information available. Click "Fetch funding" to run a targeted funding scan.

Team (5+)

Iris Lin

Marketing strategies / Digital transformation / Tech, E-commerce / Internet

Company Description

Problem

Creating and managing data pipelines for business intelligence (BI) and artificial intelligence (AI) applications can be complex and time-consuming, often requiring extensive programming knowledge and specialized skills. This complexity can hinder organizations from efficiently processing and analyzing data, leading to delays in accessing valuable insights.

Solution

Yaetos offers an open-source data framework designed to simplify the creation of data pipelines for BI and AI. The framework allows data engineers, scientists, and analysts to focus on business growth by streamlining the data pipeline process. It integrates a suite of modern data and analytics tools within a cloud environment, enabling users to build a "data engine" without needing in-depth programming expertise. Yaetos promotes modern development practices like CI/CD and GitOps, integrating open-source tools such as Pandas and Spark.

Features

Simplifies data pipeline creation with minimal programming knowledge, while providing access to the full Python environment for advanced users.

Integrates with open-source tools like Pandas and Spark for data transformation.

Supports modern development practices such as CI/CD and GitOps.

Designed for cost efficiency by encouraging the use of a data lake and utilizing resources billed only for computation time.

Can extract data from various sources, including databases, REST APIs, and SaaS services (e.g., Salesforce, Stripe).

Supports data transformations in SQL or Python.

Compatible with small, normal, and big data volumes.

Target Audience

The primary users are data engineers, data scientists, and analysts across various industries who need to build and manage data pipelines for BI and AI applications.