Data Analytics Data Lake Experimentation 
AWS Big Data
JANUARY 15, 2025
In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. This approach supports both the immediate needs of visualization tools such as Tableau and the long-term demands of digital twin and IoT data analytics.
AWS Big Data
JULY 20, 2023
With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.
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AWS Big Data
DECEMBER 12, 2024
One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios.
Corinium
JUNE 6, 2019
For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. 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.
CIO Business Intelligence
NOVEMBER 4, 2022
The company’s multicloud infrastructure has since expanded to include Microsoft Azure for business applications and Google Cloud Platform to provide its scientists with a greater array of options for experimentation. Much of Regeneron’s data, of course, is confidential. That’s hard to do when you have 30 years of data.”
AWS Big Data
JUNE 20, 2023
Apache Iceberg is an open table format for very large analytic datasets. It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Mikhail specializes in data analytics services.
CIO Business Intelligence
DECEMBER 6, 2023
We collect lots of sensor data on machine performance, vibration data, temperature data, chemical data, and we like to have performative combinations of those datasets,” Dickson says. Dickson says that DS Smith also plans to use virtual private clouds for some corporate data, giving it flexibility and control.
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