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Data management and advanced analytics are both critical capabilities. However, these two disciplines have largely been run separately.

Big Data Management

Data management processes typically involves activities such as data sourcing, cross-referencing, and ironing out any discrepancies via reconciliations and data cleansing.

Data analytics processes are typically carried out afterwards in a variety of desk-level tools and libraries, close to the business users and typically operating on separately stored data subsets.

This divide has generated problems for many financial institutions, with the separation impacting time to insight, causing data quality concerns, and hampering the decision-making processes that drive business success.

Alveo’s solutions integrate market and reference data management and the analytics that feeds off that data.

Banking Alveo
Banking Alveo

With Alveo’s business user enablement, clients can democratise analytics, bringing it into the orbit of those who are not data experts and allowing them to self-serve.
Specifically, Alveo:

  • Manages price consolidation and construction of derived data such as curves through Ops360
  • Empowers business users to define custom rules for derivation and validation without the need of IT
  • Reduces time to market of new data requirements by enabling business users to manage & customize internal and vendor data models using Ops360
  • Allows business users to directly access the market data using open-source technology using Apache Spark and notebooks

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The integration of data management and analytics enables organisations to reduce data spend, improve and transparently track data quality and streamline data sourcing and data access. It allows firms to lower the cost of data integration, switching, changes and ongoing maintenance and provides control over future cost of change by gaining oversight into how and where data is being used across the organisation.

More Insights on Business User Enablement

FRTB: Cloud to Cloud

In this report, authored by Alveo and Vector Risk, we discuss resolving the challenges of data intensity and computational complexity.

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