As a key component for making informed business decisions, asset managers rely heavily on data’s accuracy to help take their firm’s growth to the next level in this ever evolving and competitive environment. However, there are many that still manage their data manually, resulting in a number of challenges that significantly increase the possibility of error – especially as data’s volume and variety continues to rise.

Traditional methods of data management tend to involve firms’ use of multiple platforms from different providers in their effort to create “custom solutions,” which in turn causes the loss of data federation due to the siloed consumption of data by various teams. Since this fragmentation often lends itself to the creation of separate data sets, errors can result when performing mission-critical tasks like reporting and valuation.

Even asset managers that use some sort of internal primitive data warehouse lack conviction in their data due to poor quality and lack of lineage, time-consuming data extraction and opaque data management. But as managers continue to prioritize exposure to different industries, geographies and asset classes, it has become clear that they can no longer rely on their esoteric systems and manual processes. Instead, they must look to implement an enterprise cloud-based data warehouse solution that can provide them with a stronger degree of control over their data – helping them to move further up the data maturity curve and on the path toward accelerating their digital transformation.

When selecting a data warehouse solution, asset managers should seek one that provides:

  1. Asset Coverage: The capacity to handle multiple asset classes while creating coordination between the front, middle and back office.
  2. Comprehensive Reporting: The ability to manage out-of-the-box dashboards and multi-functional reports while improving data quality, regulatory and client reporting, analytics, OMS, etc.
  3. Enhanced Data Management/ETL: Embedded data quality checks, front-to-back data lineage, data cataloging, data storage for performance optimization, tracking of data load times and errors, fully transparent ETL, etc.
  4. Enhanced Analytics: A deep level of available analytics with capabilities to configure different views and filters or make any kind of changes.
  5. Ad Hoc Reporting: Complete control over data with the advanced generation of reports and ability to make changes instantaneously.
  6. Performance Attribution: The ability to calculate performance attribution and change any configurations or hierarchies for more meaningful analysis.
  7. IR Extension: Support for fully customizable ad hoc reports with the flexibility to create daily, weekly, quarterly, or “any time” period-based reports as required.
  8. Built-In Compliance: Flexibility to configure compliance rules and ability to handle multiple data sources.

In short, the possession of a robust data warehouse solution not only reduces the complexity of firms’ technical infrastructure, but it also empowers users to unlock hidden value from their data sets – all while evolving alongside business and data needs. It features integrated modules that are enhanced with strategy-aware dashboards, optimized workflows, advanced performance tracking capabilities as well as streamlined reporting and analytics capabilities, thus providing firms with predictive insights for more strategic decision-making.

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