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Data Mesh Architecture on Cloud for BI, Data Science and Process Mining

Data Science Blog

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Process Mining offers process transparency, compliance insights, and process optimization.

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Introducing the Topic Tracks for ODSC East 2024?—?Highlighting Gen AI, LLMs, and Responsible AI

ODSC - Open Data Science

Introducing the Topic Tracks for ODSC East 2024 — Highlighting Gen AI, LLMs, and Responsible AI ODSC East 2024 , coming up this April 23rd to 25th, is fast approaching and this year we will have even more tracks comprising hands-on training sessions, expert-led workshops, and talks from data science innovators and practitioners.

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Introducing the Topic Tracks for ODSC West 2023?—?Highlighting Gen AI and LLMs

ODSC - Open Data Science

Introducing the Topic Tracks for ODSC West 2023 — Highlighting Gen AI and LLMs As we progress towards the end of the year, we’re turning our full attention to ODSC West coming to the heart of the AI boom (in-person) or your computer (virtual) from October 30th — November 2nd.

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Object-centric Process Mining on Data Mesh Architectures

Data Science Blog

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. This aspect can be applied well to Process Mining, hand in hand with BI and AI. Click to enlarge!

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Data science vs data analytics: Unpacking the differences

IBM Journey to AI blog

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

Data science solves a business problem by understanding the problem, knowing the data that’s required, and analyzing the data to help solve the real-world problem. Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with.

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How Cloud Data Platforms improve Shopfloor Management

Data Science Blog

In the era of Industry 4.0 , linking data from MES (Manufacturing Execution System) with that from ERP, CRM and PLM systems plays an important role in creating integrated monitoring and control of business processes.