Scalefree  Case Studies Manage Self-Service BI for Useful Reporting

About the Client

Client is a privately owned bank and was founded in 1590. It is one of Europe’s leading private banks with 1600 employees in different departments. Its headquarters is located in Hamburg where it is led by managing partners. It has offices in Frankfurt, London, New York and Zurich, among other financial centers.

Problem Statement

For faster results the bank wanted to provide their users the ability to build and adapt their own self-service BI platform without the need of IT support. Moreover, it also wanted to build a data warehouse that would be capable of producing internal and external reports from a single source while also displaying all relevant data from across the enterprise.

The current database did not support the above use cases due to its following design constraints:

  • Data quality and scalability
  • Single-table storage systems with huge amounts of data were harder to maintain

The Challenge

To implement the data vault based solution to solve the problem there were the following challenges that had to be overcome:

  • Limited memory to store data
  • The code was not accessible to everyone
  • Due to limited disk storage, complex calculations become a problem

The Solution

The client was offered a solution from Scalefree that included:

  • An agile approach to manage projects into fixed-length sprints
  • A high performance system regardless of volume and velocity
  • A flexible data model that has no limitation to add new data and refactor existing data
  • A reference architecture that has the capability to support big data concepts and supports the integration of NoSQL data sets and real time data

Tangible Results for the Client

The project provided the following results for the bank:

  • The bank was able to create auditible solutions
  • Fully-automated parts of the data warehouse were able to help the client make less errors as compared to manual development of SQL statements and ETL processes
  • The bank was able to achieve a higher level of data security and privacy

Technologies used

  • MID
  • AnalytixDS
  • Wherescape
  • Excel
  • Tableau
  • SaaS
  • QlickView

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