About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Bloomberg Escalates Collaboration to Extend Customer Access to Cloud Data

Subscribe to our newsletter

Bloomberg continues to invest in the cloud and meet its mission of providing efficient access to data in the cloud through a collaboration with Databricks, a data and AI company, that allows mutual customers to access Bloomberg’s data offerings using Data License and its cloud-based data management solution Data License Plus (DL+).

Databricks, Google Cloud BigQuery, Snowflake

This is not a one-off arrangement, with Bloomberg recently releasing the integration of DL+ with Google Cloud’s BigQuery, and earlier this year a Bloomberg DL+ Snowflake Native App. To find out more about Bloomberg’s approach to cloud, Data Management Insight spoke to Don Huff, global head of client services at Bloomberg Data Management Services.

Huff says: “For the past couple of years, there has been a rush to cloud, but when you get there, there are still different platforms and different use cases. Databricks is used mostly for research and can analyse large amounts of data very well. Customers may also be using Snowflake or BigQuery in their workflows.”

DL+, a privately hosted, cloud-based data management solution, addresses these issues by aggregating, organising and linking licensed Bloomberg data from multiple delivery channels. It then delivers the data to applications and data warehouses in a consistent, transparent, and controlled model.

Unified Data Model

Huff says DL+ is a strategic initiative for Bloomberg and a solution that resonates with customers. Behind its success is the company’s underlying Unified Data Model, which has been developed by Blooomberg Data Management Services over some years and is based on an interoperable data mesh. Huff comments: “Our value proposition is the United Data Model. With DL+, we can do 80% of the data management customers want to do and take the pain out of their cloud journey.”

By acquiring then modeling data into inter-linked data tables, DL+ makes it easy to deliver the tables, which are ready-to-use, directly into a client’s Databricks architecture – the same goes for Google Cloud’s Big Query and Snowflake. Subsequent refreshes of the data will push updates to the Databricks workspace, along with revisions to the previous day. The key here is the modeling of the data that makes it ready-to-use, even if it comes from many different files or delivery channels.

Amazon Redshift

With Snowflake, BigQuery and Databricks integrations in place, Huff says Bloomberg is likely to partner next with the Amazon Redshift cloud data warehouse, although he notes the company will go where customers want to go. By way of example, he cites work with Cloudera that has attracted customers.

Huff concludes: “There will be further investment in DL+. Customers are doing great things with it, and Bloomberg will continue to add data content, destinations and lineage.”

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: Generative and Agentic AI in Financial Markets: What the Data Really Shows

Date: 15 October 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes Artificial intelligence is reshaping financial markets – but the reality on the ground is more nuanced, more uneven, and more instructive than the headlines suggest. A new A-Team Insight research programme, drawing on responses from senior AI decision-makers at...

BLOG

Why Sanctions Compliance Is Becoming an Intelligence-Led Discipline

By Theodora Papadimitropoulou, Head of Global Product Strategy, GTM at Dun & Bradstreet. For years, sanctions compliance was closely associated with a single task, running a counterparty’s name against the relevant lists, checking for a match and acting if required. How much that tells you, though, depends heavily on the provider and the data behind...

EVENT

Data Management Summit London

Now in its 17th year, Data Management Summit (DMS) London returns In April 2027, to explore how to use data and AI to drive measurable business outcomes reliably, repeatedly and at scale.

GUIDE

Regulatory Data Handbook 2026 – Fourteenth Edition

Welcome to the fourteenth edition of A-Team Group’s Regulatory Data Handbook. Supervisors increasingly expect firms to demonstrate which rules apply, which data supports each obligation, who owns the control and how exceptions are identified and resolved. Policies and implementation programmes must now be supported by records that can withstand regulatory scrutiny. This edition examines material...