Suppliers
United States
DataRobot
Overview
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DataRobot |
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United States | |
Boston | |
2012 | |
Private | |
$10-100m | |
201 - 1,000 | |
Open website |
IoT Snapshot
Technology Stack
Case Studies
Number of Case Studies53
Demystifying Data Science: A Case Study on DemystData and DataRobot
DemystData, a New York-based software company, is dedicated to demystifying data for its clients, particularly financial institutions. Despite the increasing use of data in the financial sector, it is still heavily underutilized, leading to business decisions being made based on suboptimal or incomplete data. DemystData aims to close this gap by providing clients with access to new and more data. However, as datasets grow larger and data sources become more varied, the complexity increases, leading to more time-consuming work for the limited pool of data science resources at the company. The challenge was to manage this increasing complexity and workload without compromising the quality of data analysis and insights. |
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Accelerates Data Discovery, Testing, and Deployment
As datasets get bigger and data sources more varied, complexity increases and work processes become more time-consuming. Demyst clients need help identifying which external data attributes are predictive in marketing, risk, and portfolio management use cases across the vast ocean of external data. |
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84.51° Enhances Personalized Shopping Experience for Kroger Shoppers with DataRobot
84.51°, a retail data science, insights, and media company, was faced with the challenge of creating more personalized and valuable experiences for shoppers across the path to purchase. This included the entire customer journey, from initial awareness to activation, retention, and beyond. The company's goal was to leverage 1st-party retail data from over 62 million U.S. households to fuel a more customer-centric journey. However, the sheer volume of data and the complexity of creating personalized experiences for such a large customer base presented a significant challenge. The company needed a solution that would enable better production, deployment, and interpretation of data science models to meet its objectives. |
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