DataRobot Blog

MARCH 8, 2023

Leveraging DataRobot’s JDBC connectors, enterprise teams can work together to train ML models on their data residing in SAP HANA Cloud and SAP Data Warehouse Cloud, as well as have an option to enrich it with data from external data sources.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

Cloudera

OCTOBER 4, 2023

On top of these core critical capabilities, we also need the following: Petabyte and larger scalability — particularly valuable in predictive analytics use cases where high granularity and deep histories are essential to training AI models to greater precision. Kudu has this covered. appeared first on Cloudera Blog.

Data Warehouse 89

Data Warehouse Experimentation Cost-Benefit Dashboards 89

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. They can also transform the data, create data models, visualize data, and share assets by using Power BI.

Big Data 125

Big Data Data Analytics Analytics Predictive Modeling 125

Corinium

APRIL 25, 2019

Then you can be more confident you’re protecting that data in the right way, in the right places, via protection policies that keep it safe without getting in the way of the business getting value from that data. The protection policy follows the data. This is a much more proactive and scalable model.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Occam's Razor

FEBRUARY 7, 2011

Benjamin Rodde: I'd like to predict our Daily/Weekly/Monthly churn using the #GooglePredictionsAPI with unique visitors from #GoogleAnalytics. The best option is to hire a statistician with experience in data modeling and forecasting. because the data is so very not available. If you have Web Analytics 2.0

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

DataRobot

JANUARY 20, 2022

— Snowflake and DataRobot AI Cloud Platform is built around the need to enable secure and efficient data sharing, the integration of disparate data sources, and the enablement of intuitive operational and clinical predictive analytics. Building data communities. . Looking forward through data.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145