Let Scientists Work with your Data
Easy-to-use toolkit for data-scientists


DataFlow — all-in-one platform for data processing. Track the work from the moment of data acquisition up to the implementation of machine learning models.
DataFlow helps managing calculations on the Hadoop-cluster like on the local machine: easily and quickly.
Use familiar Jupyter and Zeppelin notebook interfaces and implement the results of machine learning to your business processes in a few clicks.
Get the full power of Big Data tools in one intuitive and modern Web interface for better productivity.
DataFlow UI
DataFlow is the unique platform built to analyze Big Data natively on Hadoop cluster, without moving data
LEt Dataflow Solve all your problems
Data-engineers, DevOps and developers have their technology stack such as
Java, Scala, own Scheduler, etc. Using these tools they bring the models of Data-scientists into production.

Data-scientists use Python with its excellent libraries.
After creating a model on the local machine, it should be transferred to the Hadoop-cluster.

Data Loss
Data-scientists cannot access the necessary data directly, understand how data is stored on the cluster and be aware about the type of data which is currently available

Loss of Accuracy
Accuracy of calculations was lost during the transfer from Python to Java/Scala.
KPI was reached on the local machine, but was unpleasantly far away from the one on the cluster

Waste of Time
Difficulties in communication between data-scientists and data-engineers; long time-to-market, and other difficulties of modeling without DataFlow
We wanted to make the life of each Data-scientist happier
and developed DataFlow!
For many years we use Hadoop.
And every day we faced the same routine tasks. Performance of the tasks required interaction of many people
We wasted time, money and were eager to stop routine work. That's why we started automatization and created many amazing tools.
Then we developed very intuitive and user-friendly interface for the tools. By that we started the era of DataFlow – easy-to-use modeling environment
DataFlow is a powerful analytical tool for a wide variety of Big Data use cases such as trade surveillance, 360-degree customer profile, portfolio analysis, cybersecurity and and much more!
  • Optimal focus of resources and efforts
  • Leverage data profit
  • Payroll structuring
  • Awareness about the work of your employees
  • Integration with any analytical systems

  • Raise the number of working models
  • Reduce model development time
  • Increase speed and accuracy
  • Be aware about the number of working, broken models and their schedule
  • Check the reports and get notifications

Data scientist
  • One toolkit with friendly interface for all the tasks
  • Fast and easy model implementation
  • Easy-to-use modeling environment
  • Access to all the data from different sources
  • Clear result and high accuracy without excessive intervention
  • Move business forward
  • Reduce time to market
  • Increase sales and profits
  • Rapidly turn insights into actions
  • Be the first to respond to changing market
  • Plan correct marketing strategies
What do I need to use DataFlow?
Only Hadoop-cluster and desire to automate routine work.
What should I know to work with DataFlow?
Python + SQL. In addition Pyspark to create calculations on the cluster.
Can I use SciKit-Learn on the cluster?
Yes, that's the whole point! Convinient local tools to work with the cluster.
How many data-engineers I need to support the platorm?
We think that Data-Scientists should be fully responsible for data, that's why no data-engineers required.
Any quantity limitations for the number of calculations?
DataFlow does not set any limits. The number of calculations depends only on the computation capacity of your cluster.
I know Python, but never dealt with the Hadoop-cluster?
Feel free to contact us - we will show you how!
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DataFlow 2-months free trial account
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