Remove Business Intelligence Remove Data Engineering Remove IoT Remove Performance
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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. The authors state that the target audience is technical people and, second, business people who work with technical people. Nevertheless, I strongly agree.

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6 Frontiers for Data Virtualization in 2021

TIBCO - Connected Intelligence

Imagine you’re a data engineer at a Fortune 1000 company. Your company has thousands of databases and 14,000 business intelligence users. You use data virtualization to create data views, configure security, and share data. One: Streaming Data Virtualization. All this data is in motion.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

Altexsoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

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Supply Chain Analytics: Opportunities in Data Analysis and Business Intelligence

Altexsoft

diversity of sales channels, complex structure resulting in siloed data and lack of visibility. These challenges can be addressed by intelligent management supported by data analytics and business intelligence (BI) that allow for getting insights from available data and making data-informed decisions to support company development.

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Supply Chain Control Tower: Enhancing Visibility and Resilience

Altexsoft

to see where freight is in real time and what the ETA is, share this information with customers, monitor and analyze fleet/carrier performance, and much more. Previously, control towers were seen as multi-faceted dashboards to monitor performance. The readings from IoT sensors and other connected devices (e.g.,

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What is Streaming Analytics: Data Streaming, Stream Processing, and Real-time Analytics

Altexsoft

With the uprise of internet-of-things (IoT) devices, overall data volume increase, and engineering advancements in this field led to new ways of collecting, processing, and analysing data. As a result, it became possible to provide real-time analytics by processing streamed data. Batch processing.

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ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

Altexsoft

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. But even for experienced data engineers, designing a new data pipeline is a unique journey each time. Data engineering in 14 minutes. Data availability. ELT vs ETL.

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