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The Complete Collection of Data Science Books – Part 1

KDnuggets

Read the best books on Programming, Statistics, Data Engineering, Web Scraping, Data Analytics, Business Intelligence, Data Applications, Data Management, Big Data, and Cloud Architecture.

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Data Engineering – Concepts and Importance

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction First of all, we are surrounded by data in day-to-day. The post Data Engineering – Concepts and Importance appeared first on Analytics Vidhya.

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Book your Seats now for Upcoming DataHour Sessions!

Analytics Vidhya

The post Book your Seats now for Upcoming DataHour Sessions! Hence the demand of the professionals of this field is rising exponentially and Analytics Vidhya is bridging this gap by training and providing necessary aids to the aspiring tech enthusiasts. Keeping this goal in mind, Analytics […]. appeared first on Analytics Vidhya.

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Forget Streamlit: Create an Interactive Data Science Dashboard in Excel in Minutes

KDnuggets

Insert a data table if required. Step 7: Test Your Dashboard Functionality Tests: Select Books category + North region + Bob salesperson from Slicers. These steps will help you create sophisticated dashboards that provide real business value without touching a single line of Python code. Place charts at the bottom.

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10 Best Data Engineering Books [Beginners to Advanced]

Pickl AI

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. Lakhs to ₹ 20.0

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Dimensional Data Modeling in the Modern Era: A Timeless Blueprint for Data Architecture

ODSC - Open Data Science

Dimensional Modeling (the focus here): A balanced approach tailored for analytics and business intelligence. Its essential to align the model to the use case: normalized models support auditing and operational consistency; denormalized ones enable rapid data consumption. They reflect it.

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Exploring the fundamentals of online transaction processing databases

Dataconomy

Concurrency algorithms are used to ensure that no two users can change the same data at the same time and that all transactions are carried out in the proper order. This helps prevent issues such as double-booking the same hotel room and accidental overdrafts on joint bank accounts.

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