Fusion, JP Morgan’s cloud-native data platform for institutional investors has launched an end-to-end containerised data solution that models and normalises data “across multiple providers, sources, types and structures”. According to a press release from JP Morgan, the new product was designed to provide investors with “consistent and enriched data across business services”.
Siloed, inconsistent, and incomplete data presents a challenge for institutional investors who are managing data at scale across their organisations and within their operating models, writes JP Morgan. The need for “strong and scalable data foundations” only becomes more pressing as firms adopt advanced analytics, AI, and machine learning (ML).
Investors can integrate containerised data for custody, fund accounting, and the middle office using Fusion’s Data Mesh solution, which supports cloud-native channels including API, Jupyter notebooks, Snowflake, Databricks, and more. The data received is “fully harmonised across both public and private access”, and is ready for analysis and integration into the client’s workflows.
With its enhanced data catalogue, data dictionary, and semantic layer, the solution provides clients with the foundation needed for successful AI and ML implementation.
