AWS Big Data

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. This will open the ML transforms page.

Insurance 81

Insurance Visualization Data Lake Metrics 81

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. Data coming from machines tends to land (aka, data at rest ) in durable stores such as Amazon S3, then gets consumed by Hadoop, Spark, etc. There are models everywhere.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

Cloudera

FEBRUARY 4, 2019

Stream Processing – Manage and process multiple streams of real-time data using the most advanced distributed stream processing system – Apache Kafka. Process millions of real-time messages per second to feed into your data lake or for immediate streaming analytics.

IoT 72

IoT Prescriptive Analytics Digital Transformation Internet of Things 72