Cloudera
JUNE 27, 2023
The way to achieve this balance is by moving to a modern data architecture (MDA) that makes it easier to manage, integrate, and govern large volumes of distributed data. When you deploy a platform that supports MDA you can consolidate other systems, like legacy data mediation and disparate data storage solutions.
CIO Business Intelligence
OCTOBER 4, 2022
It’s yet another key piece of evidence showing that there is a tangible return on a data architecture that is cloud-based and modernized – or, as this new research puts it, “coherent.”. Data architecture coherence. Putting data in the hands of the people that need it. The study results don’t surprise us.
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IBM Big Data Hub
SEPTEMBER 19, 2023
Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.
CIO Business Intelligence
JULY 26, 2023
“The only thing we have on premise, I believe, is a data server with a bunch of unstructured data on it for our legal team,” says Grady Ligon, who was named Re/Max’s first CIO in October 2022. We made a commitment to be truly cloud native and build an architecture that wasn’t burdened by any legacy infrastructure,” says Cox.
IBM Big Data Hub
MARCH 7, 2023
The specific approach we took required the use of both AI and edge computing to create a predictive model that could process years of anonymized data to help doctors make informed decisions. We wanted to be able to help them observe and monitor the thousands of data points available to make informed decisions.
Data Science 101
JUNE 10, 2019
Data scientists are the bridge between programming and algorithmic thinking. A data scientist can run a project from end-to-end. They can clean large amounts of data, explore data sets to find trends, build predictive models, and create a story around their findings. Data Analysts.
Alation
APRIL 25, 2023
As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. 5 common data governance mistakes 1.
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