Cloudera
AUGUST 8, 2022
The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Cloudera Data Engineering (Spark 3) with Airflow enabled. Cloudera Machine Learning .
AWS Big Data
JULY 27, 2023
Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.
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Hurwitz & Associates
MAY 15, 2018
To meet that challenge, Cloudera is now embarking on a major transition in its strategy that requires it to hold on to its predominant position in Hadoop analytics – and to become a provider of machine learning software supporting both on premises and public clouds. Why focus on the Global 2000 accounts? Going Forward.
Peter James Thomas
AUGUST 18, 2018
That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. These people take on much of the heavy lifting of consolidating, fixing and enriching datasets, allowing the Data Scientists to focus on Statistical Analysis, Data Mining and Machine Learning. In Closing.
Cloudera
DECEMBER 12, 2018
And then I moved from Madison, Wisconsin to San Francisco in 2000, to chase the dotcom dream. After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. Let’s talk about big data and Apache Impala. Michael Moreno: Nice!
Sisense
FEBRUARY 24, 2021
In fact, in a 2019 edition of Industrial Management & Data Systems, a research team led by Yu Nie noted that prior to the year 2000, there were only six chief data officers in the world. Clearly, data is becoming more important to organizations. This is one approach to solving the challenge of data silos.
Corinium
APRIL 25, 2019
The areas of fastest AI innovation and adoption are around machine learning, using it for more and more use cases where there exists large volumes of data, and human beings just don’t have the bandwidth or can’t keep up with ongoing stream of transactions, events, or whatever other changes in the environment being described by that data.
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