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And the 2018 EMEA Partner Summit Award Winners are…

Cloudera

Last week Cloudera hosted over 150 attendees at our annual EMEA Partner Summit in Amsterdam with attendees from over 21 countries across the region. The post And the 2018 EMEA Partner Summit Award Winners are… appeared first on Cloudera Blog. Training Partner of the Year – Xebia, France.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of data, analytics, and machine learning. Temporal data and time-series.

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Take Your SQL Skills To The Next Level With These Popular SQL Books

datapine

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

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Meet the newest Data Superheros: The Sixth Annual Data Impact Awards Finalists Are…

Cloudera

From AI models that power retail customer decision engines to utility meter analysis that disables underperforming gas turbines, these finalists demonstrate how machine learning and analytics have become mission-critical to organizations around the world. Brian Carpenter , Co-Host, The Hot Aisle Podcast, @intheDC.

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The future of casino marketing strategy is digital plus data

BizAcuity

In 2018, the US Supreme Court’s decision to legalize sports betting was historic. Thanks to data analytics, these decisions can now be backed by data. Real-time decisions can be taken in line with data insights. Casino owners can also leverage similar approaches using data analytics. Player Churn.

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How to use Netezza Performance Server query data in Amazon Simple Storage Service (S3)

IBM Big Data Hub

This data will be analyzed using Netezza SQL and Python code to determine if the flight delays for the first half of 2022 have increased over flight delays compared to earlier periods of time within the current data (January 2019 – December 2021). Figure 7 – Initial query using the historical data (2003 – 2018).

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Preprocess and fine-tune LLMs quickly and cost-effectively using Amazon EMR Serverless and Amazon SageMaker

AWS Big Data

Filter data from the Common Crawl dataset As you can see from the create table SQL statement, there are several fields that can help filter the data. After you have prepared the data and scripts, you can use EMR Serverless to process the filtered data. Delete the SageMaker endpoint that hosts the LLM model.