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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.

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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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What is Data Engineer: Role Description, Responsibilities, Skills, and Background

Altexsoft

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

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Enabling privacy and choice for customers in data system design

Lacework

This is particularly relevant when the data potentially includes user information, and the architecture must ensure hosting of the data complies with customer preferences or regulatory requirements regarding where the data is hosted. What regional data requirements or preferences should be considered?

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5 hot IT budget investments — and 2 going cold

CIO

This includes spending on strengthening cybersecurity (35%), improving customer service (32%) and improving data analytics for real-time business intelligence and customer insight (30%). This applies to his IT group as well, specifically, in using AI to automate the review of customer contracts, Nardecchia says.

Budget 363
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Data analytics: your complete guide to big data consulting

Agile Engine

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Table of contents 1.

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ETL vs ELT: Key Differences Everyone Must Know

Altexsoft

ETL and ELT are the most widely applied approaches to deliver data from one or many sources to a centralized system for easy access and analysis. With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g Both consist of the extract, transform, and load stages. What is ETL?