Corinium

JUNE 6, 2019

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. It is also important to have a strong test and learn culture to encourage rapid experimentation.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 84

Machine Learning Modeling Metadata Recreation/Entertainment 84

DataKitchen

JANUARY 17, 2022

The dynamic nature of data leads to complexity, including significant quality control (QC) challenges. Testing and validating analytics took as long or longer than creating the analytics. Business analysts needed the flexibility that comes with control of data and orchestrations. Data is not static.

Experimentation 130

Experimentation Data Lake Marketing Predictive Modeling 130

Cloudera

JUNE 6, 2019

While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Now the admins need to synchronize multiple copies of the data and metadata and ensure that users across the many clusters are not viewing stale information.

Metadata 86

Metadata Data Lake Strategy Optimization 86

DataRobot Blog

MARCH 7, 2023

DataRobot on Azure accelerates the machine learning lifecycle with advanced capabilities for rapid experimentation across new data sources and multiple problem types. Customers can build, run, and manage applications across multiple clouds, on-premises, and at the edge, with the tools of their choice.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data.

OLAP 87

OLAP Data Lake Data-driven Snapshot 87