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Democratizing
Big Data Analytics

For Big Data & Lakehouse Architectures

All the power of 
without the <coding>

All the power of  without the <coding>

We deliver the power of  

We deliver the power of  

EFFICIENTLY

&

INTERACTIVELY

Distributed,
Scalable

Semi-structured &
Unstructured Data

Streaming &
Batch

ML &
Graph Analytics

Hybrid &
Multi-cloud

By utilizing Drag & drop to build big data pipelines in hours not weeks

Data preparation in Scala & AI/ML in Scala/Python/R as needed

Cluster vs. legacy ETL server

Drag & Drop

Breakpoints + Full
interactive debugging

Examine interactive data samples
from any source & after
each processing stage

export JAR for production
Jar

BUSINESS BENEFITS

Enable big data access & processing , for everybody

Minimize time to insights - from lengthy weeks to few hours

Hybrid
(private & public cloud)

Cloud Agnostic

Efficient machine learning deployment to production.

Future proof: Leading open-source Spark infrastructure

No-Code Apache Spark Big Data Pipelines for BI Analysts & Data Scientists

In this WP, you will learn about:

value for

Data Architect

Democratise big data access and processing, empower your analytic teams, reduce long and costly R&D processes, and benefit from a Hybrid & Cloud agnostic data processing solution

BI Analyst

Easily process big & modern data, build big data pipelines in hours instead of weeks or months, and enjoy smooth integration with the data science team.

Data Scientist

Integrate big data pipelines with Jupyter Notebook, utilize Spark MLlib, easily generate pipeline deployments, and deploy Python to production.

Data Engineer / DevOps

Build data pipelines and execute them within a matter of hours, and not weeks.

Some of our Partners

Resources