Remove Big Data Remove Data Integration Remove Deep Learning Remove Measurement
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Core technologies and tools for AI, big data, and cloud computing

O'Reilly on Data

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. AI and machine learning in the enterprise. Deep Learning. Data Platforms.

Big Data 209
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The quest for high-quality data

O'Reilly on Data

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Data integration and cleaning.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

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Data Analytics for Crypto Casinos: Significance and Challenges

BizAcuity

It also means heavy investments on data storage, management, security and speed at which data should be processed. A lot of investments go into data warehousing, big data management and data storage to ensure revenue is not lost due to any glitches or misconfiguration.

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Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Data is on the move. We keep feeding the monster data.

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The DataOps Vendor Landscape, 2021

DataKitchen

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix. Azure DevOps.

Testing 300
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How to accelerate your data monetization strategy with data products and AI

IBM Big Data Hub

Data monetization is not narrowly “selling data sets ;” it is about improving work and enhancing business performance by better-using data. External monetization opportunities enable different types of data in different formats to be information assets that can be sold or have their value recorded when used.

Strategy 111