DWH framework: manage your data warehouse efficiently

Modern data warehouses process data in batch and real-time, store it in the cloud, and enable creation of analysis and reporting using natural language queries.

They are the repository for all the structured enterprise data your business needs for analysis and management. They can be easily extended with Data Lake, all repositories can be logically linked and used together.

Advanced analytics including machine learning and artificial intelligence can process data in both structured and unstructured form. In addition, development and management costs, including the cost of buying technology, are continuously decreasing.

59 %

V roce 2015 využívalo big data jen 17 % společností. O pouhé tři roky později, v roce 2018 to bylo již 59 % firem.

Latest trends in DWH

  • The technology and architecture of big data is becoming a mainstream alternative to traditional databases when it comes to the use of Business Intelligence.
  • The technology of using natural language and streaming data is growing significantly and transforming the market.
  • Most organizations are gradually moving all critical data and applications to the cloud.

The main components of Adastra's DWH are independent of specific technologies.

DWH by Adastra

Our DWH solution includes

  • Data integration - we ensure the collection and consolidation of data from different data sources.
  • Data warehousing - we will set up the optimal storage of the necessary data and its use.
  • Metadata repository - we link data information for more efficient use.

Above the DWH itself, we allow you to build two more layers:

  • Business Intelligence - used for data analysis and report creation. It also allows you to do data visualization, self-service Business Intelligence, performance measurement, mobile Business Intelligence, predictive analytics, data mining and more.
  • Applications - you can use for example for campaign management, fraud detection, risk management, enforcement, application approval, etc.

The DWH architecture we build for our clients

  • provides understandable information to different groups of users for different purposes,
  • enabling regular reporting and flexible ad-hoc reporting and analysis,
  • leverages knowledge and experience from many data warehouse building projects in different organizations,
  • correspond to the latest trends,
  • helps companies to train their own DWH experts who will take care of the effective use of the delivered solution.
50 %

IKEA has halved the time it takes to search for data on goods customers have bought, for example for returns or complaints, following the introduction of a new data warehouse. Previously, employees searched for receipts in three different systems and the process took minutes, but now it takes seconds.

DWH framework - a tool for fast and convenient data warehouse management

Do you want to store and analyse your data efficiently? The DWH framework is a tool for daily data updates and long-term optimized development, documentation, reporting and monitoring.

Traditional data warehouse management issues

The traditional way of managing a data warehouse with the usual tools relies heavily on developers. This means that there is very little control over hundreds of processes, you face reliability issues, and you must do without good documentation. This means that warehouse management:

  • is expensive
  • is error-prone and unreliable
  • complicates further development
  • has performance problems

In short, the traditional data warehouses management does not add sufficient value to management and business users who can neither rely on the data stored nor make decisions based on it.

Data warehouses managed in the traditional way do not provide enough value to management and business users because they cannot rely on the stored data to make decisions.

Adastra has developed a custom solution for fast and convenient data warehouse management. The DWH framework is based on general data warehousing principles and practices and was developed based on Adastra's long experience. This set of standards and best practices for DWH development is based on metadata.


We reduced the time it takes the insurance company Kooperativa to retrieve data from source systems from an average of 36 hours to approximately 6 hours.

Benefits of the DWH Framework

  • Significant time and effort savings (up to 60%)
  • High return on investment (Dev & SLA)
  • Reliability = quality service for the business
  • All-in-One Tool - single point of management
  • Easy customization
  • Performance optimization

Our technical features include:

  • · Support for multiple DB types, environments and data sources
  • · Support for all DWH layers (L0, L1, L2)
  • · Ready and established data governance practices
  • · Versioning support
  • · Monitoring, logging and auditing

Do you want to manage your data warehouse economically? Contact us for more information.

Thank you

We will contact you as soon as possible.

Růžena Barešová

Business Development Manager

Martin Bém

Consultant & DW Architect