Architecture Business Intelligence Survey Training 
CIO
NOVEMBER 23, 2022
Enterprise architecture definition Enterprise architecture (EA) is the practice of analyzing, designing, planning, and implementing enterprise analysis to successfully execute on business strategies. Of course, to implement any EA strategy, you will also need to ensure that you have buy-in from other executives and stakeholders.
Altexsoft
NOVEMBER 10, 2020
Business Intelligence is a practice of turning raw data into useful insights. Probably yes, as it’s the most balanced view of the business you can get. Now, let’s talk about your Business Intelligence strategy. Tools and architecture. And we’ll start with those businesses who already have some form of BI.
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Cloudera
AUGUST 27, 2024
The annual survey of hundreds of global IT decision makers assesses cloud strategies, migration trends, and important considerations for companies moving to the cloud or managing cloud environments. The cloud is ideal for workloads with intermittent or burst capacity requirements, like training AI models.
CIO
DECEMBER 20, 2023
We also have a quarterly survey, which is an important tool to help get a feeling of staff engagement and sentiment. We have ongoing training, education, and development for staff to ensure they’re upskilled in this area, both for their work life and personal life. This also helps create that greater sense of engagement and fulfilment.
O'Reilly Media - Data
JULY 23, 2018
The results of a recent survey we conducted (with 11,000+ respondents, a full report is forthcoming) bears this out—only about 15% of respondents worked for companies that have extensive experience using ML in production: In this post, I’ll describe how one can go from “exploration and evaluation” to actual “implementation” of ML technologies.
O'Reilly Media - Ideas
FEBRUARY 11, 2019
This concurs with survey results we plan to release over the next few months. In a forthcoming survey, “Evolving Data Infrastructure,” we found strong interest in machine learning (ML) among respondents across geographic regions. Machine learning and AI require data—specifically, labeled data for training models.
Exadel
FEBRUARY 27, 2023
Whether you opt for supervised machine learning algorithms that feed off structured data or deep learning networks that independently parse large volumes of unstructured information (like images, PDF documents, and social media posts) you need lots of data to train algorithms capable of solving your business problems.
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