With all of the investment companies are making in data science, it’s shocking how few see any real business impact. A recent study quantified this gap by revealing that while 85% believe models will allow their companies to obtain or sustain a competitive advantage, only 5% are using them extensively.
The reason why is simple; it’s extremely hard for companies to get models beyond their data science teams and into production. As one data science leader so astutely and memorably put it, “We built our new headquarters faster than we could deploy a model into production.”
Today, we are helping to change that with the launch of Domino 3.0, the next release of our award-winning data science platform, and the introduction of Launchpad, a new module designed to help companies maximize the impact of their data science investments by addressing the operational challenges and bottlenecks they face getting models into production (ModelOps).
Solving the last mile problem in data science
Now with Domino 3.0, companies can fill the gaps between data science investment, execution, and realizing competitive advantage by eliminating the model delivery bottleneck.
Domino’s new module, Domino Launchpad, helps companies solve the last mile problem in data science by:
The motivation behind Domino 3.0 came from working with leading data science organizations to see what worked and did not work for them. The latest Domino 3.0 functionality was built to help data science leaders ensure that their investments are yielding tangible business impact.
Moody’s Analytics improves model iteration speed by 4x with Domino
Moody’s Analytics supplies expertise and tools—including data, models, software, and professional services—that help companies grow efficiently and manage financial risk. A pioneer in financial modeling, the Moody’s Analytics team has established a competitive advantage by creating models based on unique financial data sets through a process they have honed over decades, and then applying those models to solve clients’ business challenges. By centralizing some of their data science projects on Domino, Moody’s Analytics has dramatically increased the efficiency of their model lifecycle, and expanded their ability to build collaborative models with clients and partners. To make this transformation, Moody’s Analytics needed to accelerate the pace of model development and the number of iterations they could make on models in production. They’ve accomplished this with Domino, reducing end-to-end model development cycles and delivering models to downstream consumers as APIs and applications. For example, in an early experience using Domino, Moody’s Analytics reduced an estimated nine-month project to four months. The firm has also increased production model iteration speed by four times using Domino. “With Moody’s Analytics know-how and workflow, coupled with Domino and AWS infrastructure, we have been able to accelerate model development, which means information gets into the hands of our clients who need it faster,” said Jacob Grotta, managing director of Risk and Finance Analytics for Moody’s Analytics. “Our customers are excited because their needs are going to be answered in new ways that would previously have been impossible.”
Learn more about Domino 3.0 and Launchpad
Domino was recently named a leader in the Forrester Wave report “Notebook-based Predictive Analytics and Machine Learning Solutions” by Forrester Research.
To learn more about Domino 3.0, register for the webinar, “How Leading Organizations Are Solving the ModelOps Challenge”, featuring Forrester Research, Bayer Worldwide, and Domino on November 14 at 10:00 a.m. PST. Register here.
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