by Use Case Data Warehouse Modernisation

Data Warehouse Modernisation

Many existing data systems need a makeover to support new business needs, implement data governance and become more agile.

We design and implement data warehouse solutions in a scheme that best fits to the client’s requirements and is at the same time easily scalable in order to support new analytical needs.

MODERN DATA ARCHITECTURE

CLOUD PLATFORM

  • Providing advanced analytics and artificial intelligence capabilities.
  • Delivering better-quality insights for real-time decision-making.
  • Providing high query performance to support complex analytical applications.
  • Enabling easy access to any analytics tools, business applications or user.

DATA WAREHOUSE

A central repository of integrated and consolidated data from disparate sources for data analysis and reporting.

DATA LAKE

Repository of semi-structured and unstructured data that serves as a strong data foundation for data scientists.

Data Integration Framework

Data ingestion and data integration framework with metadata-driven architecture that automate the ETL / ELT process.

END-TO-END DATA LINEAGE

A data life cycle that includes where the data originates and what happens to data as it travels through different transformations.

Sophisticated Impact Analysis

Identification of the consequences of new enhancements on the current implementation within seconds.

Custom Analytical Hierarchies

Management of custom analytical hierarchies for different business needs that are unavailable in source systems.

WHY CHOOSE US?

We can provide a pragmatic step-by-step plan and ensure a modern approach to solving complex data integration
challenges.

DataMerlin is a platform composed of proven methodology, built-in technical expertise, best practices and tools that automate the ETL / ELT process as much as possible.

Backed by 15 years of experience and more than 100 projects of data warehouse implementations, both domestically and globally and across a wide range of industries, our solution encapsulates everything we've learnt along the way.

By combining the power of automation with a metadata-driven approach, we can significantly reduce delivery time, costs, and risks and achieve greater efficiency and higher consistency of your data warehousing project.