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Neo4j > Case Studies > Data Lineage Tool Improves Risk Management, Drives Compliance
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Data Lineage Tool Improves Risk Management, Drives Compliance

 Data Lineage Tool Improves Risk Management, Drives Compliance - IoT ONE Case Study
Technology Category
  • Application Infrastructure & Middleware - Database Management & Storage
  • Cybersecurity & Privacy - Database Security
  • Cybersecurity & Privacy - Security Compliance
Applicable Industries
  • Finance & Insurance
Applicable Functions
  • Business Operation
Use Cases
  • Cybersecurity
  • Cybersecurity Services
The Challenge

UBS needed to comply with regulations put in place to strengthen systems for risk data aggregation and internal risk reporting in the wake of the 2007 global financial crisis. Specifically, UBS sought compliance with the Basel Committee on Banking Supervision issued standard 239 (BCBS 239).

UBS built an application called Group Data Dictionary (GDD) as its data lineage and data governance tool.

The first iteration was built on Oracle, but UBS soon discovered limitations with an RDBMS approach, which relies on JOINS to connect data across tables. UBS decided it needed a better solution suited to creating real-time data lineage visualizations and exporting lineage information for ad-hoc analysis via Excel.

The Customer


About The Customer

UBS is a multinational investment bank and financial services company based in Switzerland. Founded in 1862, it is the largest player in the famous Swiss banking industry. UBS maintains offices in more than 50 countries, employs more than 66,000 people, and reported total assets of more than $958 billion in 2018. UBS operates in five main business areas: personal banking, wealth management, corporate and institutional clients, investment banking, and asset management.

The Solution

UBS synchronized Neo4j with the Oracle system, starting with an initial data load and then performing an incremental sync in which transactions were read from an Oracle table and written into Neo4j in real-time.

UBS used Neo4j to evaluate data lineages and depict the results in GraphJSON. This information flows into a D3.js visualizer to render the data as a lineage diagram.

Having all the metadata makes for easy reporting. The data can be used for ad hoc reporting when specific questions arise, and entire lineages can be exported to Excel.


Operational Impact
  • [Data Management - Data Availability]

    Easier and faster compliance, with real-time queries and visualizations

  • [Data Management - Big Data Analysis]

    Deep understanding of data flows for impact analysis and governance

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