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The Future of the Data Lakehouse – Open

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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2020 Data Impact Award Winner Spotlight: United Overseas Bank

Cloudera

To drive the vision of becoming a data-enabled organisation, UOB developed the EDAG (Enterprise Data Architecture and Governance) platform. The platform is built on a data lake that centralises data in UOB business units across the organisation. To learn more about UOB please visit: [link] .

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How Can Manufacturing Data Help Your Organization?

Sisense

In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. The world of data in modern manufacturing. From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. Qualitative data benefits: Unlocking understanding.

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5 Ways Data Engineers Can Support Data Governance

Alation

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. Adopt an approach of access segregation.

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Eight Top DataOps Trends for 2022

DataKitchen

For example, a Hub-Spoke architecture could integrate data from a multitude of sources into a data lake. The Hub-Spoke architecture is part of a data enablement trend in IT. Data that flows through the Hub-Spoke data architecture will be controlled and managed by workflows located in a centralized process hub.

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Introducing watsonx: The future of AI for business

IBM Big Data Hub

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. It helps facilitate the entire data and AI lifecycle, from data preparation to model development, deployment and monitoring.