Big Data Days 2019

 October 8-10   Moscow

Pavlov Dmitriy

Arenadata, Russia

Andrey Konyaev

Arenadata, Russia


October 8, 2019






Pavlov Dmitriy

Started as an operations engineer of GPU supercomputer in 2009, I worked in data analysis and devops spheres, until in 2013 I started to explore the world of DWH. For the next four years I was head of administration of one of the most technologically advanced Fintech Data Warehouses (DWH) in Russia. Now, all the experience that I collected before, helps me to build flexible and effective data solutions for customers.
My area of interest includes, but is not limited to: analytical databases, machine learning, cluster computing, monitoring and visualizing, data pipes, etc.

Andrey Konyaev

I am a Product Owner with 8 years of experience in BigData. Strong skills in building data processing information systems and applications around them.
Now I specialize in ClickHouse – customer consulting, DB integrations, contributing to main ClickHouse open source project.


Enterprise Data Platform Based on Open Source Software: as Simple as Possible

The last few years in the sphere of data warehouses (DWH) are best described by one phrase: the game has changed. In contrast to the mono-vendor solutions of the past, the modern data landscape is not represented by a single silver bullet system, or even several systems from one vendor. A business that wants to gain a competitive advantage from the available data is forced to use dozens, if not hundreds, of various components and systems, each effectively solves its narrow task.

At the same time, there is a growing tendency to abandon vendor lock-in solutions – now companies are increasingly choosing open source solutions. This allows them to diversify the risks of contractors and vendors, simultaneously opening the door to accumulate internal expertise on technologies with their subsequent independent support.

Another trend is also becoming more noticeable – more and more companies are choosing clouds instead of their own capacities for infrastructure. A few years ago these were mostly private installations, now there is an advantage in using public ones. Each cloud provider carries its own virtualization technologies, networks and other specifics.

Such a number of technologies in one landscape raises the question of competencies: where to get the necessary number of experienced specialists in each technology? How to learn how to deploy and operate a variegated data-landscape efficiently, while remaining within the established budgets?

You will find the answer in this master class


  • Data platform concept
  • Applications and infrastructure: lets separate it
  • Install and run ADCM
  • ADCM basics (creating hosts, clusters, security)
  • Deploying monitoring cluster
  • Deploying Greenplum
  • Deploying Clickhouse
  • Clusters integration


  • The Data Platform Concept
  • Greenplum and Clickhouse deployment: monitoring, integration and other questions
  • MPP RDBMS operations in DWH landscape

Target audience

Specialists associated with the integration and operation of large data processing systems in enterprises:

  • Architects
  • Developers
  • Administrators
  • Engineers
  • Analysts

Technical requirements

None, assets will be presented in real time.