Five years ago, many firms typically deployed a data warehousing solution as an end point to centralize data collection for reporting. More recently, data warehousing has become a critical and central component of an investment firm’s architecture. Firms are positioning data warehouses as data hubs that sit in the middle of their architectures to enable data consolidation and efficient integration across disparate systems.

As business needs have become more sophisticated, and as the sheer volume and complexity of data has grown dramatically, many firms have recognized that data is the backbone of their business and that quality and timely data is essential to investment and operational success. Firms have implemented data management strategies that include firm-wide operational changes and the implementation of responsibilities and governance around data ownership. Larger investment organizations have found that a single data warehouse has become too cumbersome to support diverse business needs, and they have created data marts to support specific business objectives. Data marts contain a subset of data in a summarized or calculated form that facilitates data access and reporting and may also be supplemented with additional data that is unique to the business purpose.

Many firms use a data warehouse to support new instruments, especially derivatives. Data warehouses provide consolidated, disciplined and holistic views of their assets and security types. The data warehouse also enables enterprise reporting for portfolio and risk management purposes. For derivatives, firms use the data warehouse as storage for documentation and collateral details and as the repository to link hedged positions and view hedge effectiveness.

Vendor Offerings

There are more vendor choices today than three to five years ago. The emphasis on data in the investment industry is driving more products to be marketed as data warehouses, such as in the proliferation of reference data management platforms, which barely existed until recently.

Traditional data warehousing offerings are more mature and include enhanced functionalities, such as workflow management capabilities, expanded data coverage, i.e., derivatives, and performance measurement and performance attribution.

Reporting continues to be a challenge, although vendors are improving capabilities with additional functionalities, and many are partnering with third-party reporting vendors. Many firms that use data warehousing vendor solutions have deployed their own choices of third party reporting solutions and even built data marts to isolate selected reporting and business functions.

In addition to reporting, future plans for the data warehousing vendors include enhancing technology to support .NET or Service Oriented Architecture (SOA) and enhancing data models to support more instruments and time series data.

Investment Management Industry Practices

Most asset managers have a formal data warehouse solution in place and have had one for over three years. CutterResearch™ has found that over half of the firms with a data warehouse have built their own proprietary solutions. Those firms with third party solutions primarily use Eagle PACE. Those firms shopping today will find a broader array of systems, and many are designed and marketed to perform specific functions, whether reference data, research data, etc.

Implementations

CutterResearch has found that many firms thought the installation of a data hub would solve data problems. Most have discovered that, without a comprehensive data management strategy that involves the entire organization, the implementation will fail. Systems should be implemented after a careful evaluation of data sources, redundancies with data in other systems, and full reconciliation with data from other sources. Cutter has found that the successful deployment of a data warehouse is a multi-year effort that requires a strong partnership with the business and well-defined incremental steps that result in early wins. In a recent implementation CutterConsulting™ worked with a leading firm and began by organizing all trading information. While a small, incremental step, it gained the strong backing of traders, compliance officers and portfolio managers, and it provided the impetus to move forward with more comprehensive parts of the overall data initiative.

Conclusion

Cutter expects that data management initiatives will receive further impetus from regulations, given the data requirements inherent in the SEC’s best-execution requirements and in MiFID. In addition to the need for more robust and sophisticated client, operational and investment reporting, the requirement to better organize and understand the risks and structure of a broad range of complex securities and derivatives is driving the demand for efficient and robust data management solutions.