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Modern Data Warehousing & Business Intelligence

Introduction

Great strides have been made in the world of big data technologies over the past decade. Cloud infrastructure along with new storage paradigms like Hadoop, graph databases and message buses have provided a new dimension to the arsenal of tools available to tackle the deluge of data the world is facing.

A “modern” data warehouse architecture that combines SQL and not only SQL (NO-SQL) technologies is a preferred way to store and enrich enterprise data where “small data” is seen as latest fad, where the focus is back on quality rather than quantity.

Our view is that a well-structured data warehouse, with SQL at its core, still offers a technological maturity that is still lacking from these new world tech solutions that remains relevant to financial service provides.

Data Warehouse High-Level Architecture

The architecture for a data warehouse hasn’t changed much over the years except for the inclusion of “Big Data” sources. The figure above, outlines the layers and concerns of such an environment:

  • Source systems – Transactional and external systems used for day-to-day business operations.
  • Staging and Landing – Data is received from the source systems either by extracting data or having the source systems pushing the data into a landing area.
  • Processing – Applying business logic and rules in one central location
  • Data Warehouse – Location where the processed data is published and conformed to enterprise entities.
  • Logical Data Marts – Logical or virtual subject orientated data markets (i.e. sales, marketing, finance, etc.) that feeds off the data warehouse.
  • Presentation – Presentation layer where the business users will consume the information.

The following high-level stages are generally prescribed when implementing a data warehouse that will provide a return on investment to the business:

Contact Us

Our executive team has extensive experience in data warehousing and business intelligence in banking, credit risk, stress testing and data management. We see an overlap in these areas that provide a sweet spot for a return on investment made. If you or your team could benefit from this approach, please contact us to discuss how we can assist you and your team.

This article is available in a downloadable whitepaper:

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