Big data

Give your data a broader perspective with big data solutions. Customize information for business teams. And start generating greater profits with them.

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Bridge your data silos

Design the architecture of data solutions

Share large amounts of data across the company

Have data on hand for innovative and modern solutions

We build hybrid, cloud and on-premise platforms

Datové a analytické platformy big data jsou základem pro váš další růst.

Process not only structured but also unstructured and semi-structured data. Whether they take the form of logs, transactions, signal data, sensor data, texts, images, voices, or videos. On big data platforms, you can process all of them in any quantity and present them to end-users in the form of datamarts, feature stores, and visualization layers. As a result, you’ll start leveraging them effectively for business purposes.

Provide users with data in batches and in real-time, all in one place, so they can execute advanced analytics and AI projects at the highest level. If you’re expecting growth today, enable them to scale data and analytical solutions. And also address where to archive the data.








on-premise Big Data platforms built in Czech Republic


application and analytics projects over Big Data

Trusted by the best


Benefit from the advantages of data and analytical platforms


Acquire and store data from various internal or external sources


Work with fast-generated data


Maintain a long-term history of the data used


Consolidate data storage into one world


Reduce the load on data warehouses


Accelerate prototyping and deployment of new business solutions

Comprehensive services: from design to security

Provide your business users with a reliable big data platform. Have solutions designed and built for both structured and unstructured data, batch and streaming.

Corporate data IT infrastructure design

  • tailored architecture based on current and planned technologies
  • support for private Clouds and dockerization

Performance evaluation and suggestions for improvement

  • with regard to the types of data stored, their flows and intensity
  • efficient hardware design for specific use cases

Platform administration

  • effective cluster and user management
  • ETL job management
  • ensuring connectivity
  • pipeline deployment
  • monitoring
  • performing updates

Automation and CI/CD pipelines

  • faster development life cycle
  • maintaining code consistency and security

Data integration

  • integration of various data sources into one place
  • management of data sources

Application development for scalable data processing

  • from data acquisition through data transformation and manipulation, storage and sharing on a data platform
  • powerful metadata-driven applications

Platform security tips

  • using robust protocols and security approaches
  • guaranteed and non-guaranteed zones
  • anonymization solutions
  • GDPR compliance

Trends from Big Data London: Materialise them into innovative projects and quality project delivery

Dive into the pulse of innovation and AI trends from this premier event. Explore the key insights and takeaways that redefine possibilities.

Results of generative artificial intelligence depend on your data quality

Integrate AI in daily tasks, particularly repetitive, low-value activities.

GenAI cannot achieve quality without proper data quality. Start with that.

Apply GenAI in areas of your core strengths, e.g., avoid generating code if you’re not an expert.

Adopt hybrid cloud environments

Enhance flexibility for using cloud services.

Find support for the emergence of the open data formats, including Iceberg and Deltalake.

Easily manage multiple environments from a single location.

Turn to the lakehouse concept

Create resilient modern data architecture and break down data silos.

Separate storage and compute layers will increase efficiency and reduce costs.

Democratize data with no excuses

Incorporate metadata and data governance as key elements in creating value for a data democratization program.

Implement data-driven decision-making at all organizational levels, promoting accountability.

Create new roles to promote data democratization, such as data access governance managers.

Uphold accountability and legislation

ESG: go beyond reporting metrics and generate insights to evaluate societal impacts and quantify responsible corporate actions.

FinOps: establish disciplined approaches to managing cloud costs.

Shift your focus on role-based data access, avoiding excessive data proliferation.

How we proceed with big data projects

Evangelization and workshops

Creation of a LAB

Using the LAB for specific tasks

Custom architecture design

New production platform

Platform for daily use

We design and implement specific solutions

Add value to your data

Adoki: data replication tool

Transfer data to data warehouses, on-premise platforms, cloud, and multi-cloud. Thanks to our Adoki tool.


Data anonymization

We anonymize data sets, using our own anonymization framework for this purpose.


Data science

We implement projects utilizing advanced analytics and machine learning.


CoDET: external data sources

We develop solutions for business users – an application for enriching data from external sources.


Categoo: transaction categorization

We are developing a specific application for banks to label/categorize bank transactions.


Technologies we use

Our case studies

ŠKODA AUTO: data transfers on analytics platform are comprehensively managed and monitored by Adastra’s Adoki

In 2018-19, Adastra built an on-premise Data Analytics Platform (DAP) at ŠKODA AUTO. Its purpose? To visualize data and use advanced analytics and artificial intelligence to perform sophisticated tasks with large volumes of data.

servers use the solution implemented by Adastra

TB is the total data storage capacity

months to connect Adoki to the required data sources

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Automatic categorization for 98.5% of card transactions

With millions of clients conducting millions of operations every day, the bank needed to automatically assign a unique category to every banking transaction (card...

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Just-in-time loan offers: a 10x higher conversion rate

Together with the bank, we used several years’ worth of transaction descriptions and a number of transactions of a specific type to identify a...

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An increase in impressions among the target group: a 10x bigger target group

Online advertisers want to target their campaigns accurately and reach the right audiences. Consequently, online media operators have turned to Adastra to help them...

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Get inspired on our blog

Observability platform vs. observability tools 

Complex information systems fail in unexpected ways. That’s why IT teams need both observability tools and an observability platform. To understand the distinction between...

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What is observability? Not just logs, metrics and traces

As dynamic systems architectures increase in complexity and scale, IT teams face mounting pressure to track and respond to conditions and issues across their...

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Good data management and the gap between IT and business are the most burning issues for large Czech companies 

Large Czech companies consider the biggest challenge they will face in the next three years to be good data management and business’ inability to...

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Let's talk

Tomáš Synek
Business development director