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Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and …
While tools for analyzing streaming and real-time data are gaining adoption, the ability to visualize these data types has yet to catch up. Dashboards are good at conveying daily …
Manage your data with a system designed to support modern application development. Updated for MongoDB 4.2, the third edition of this authoritative and accessible guide shows you …
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you're comfortable with …
Data analysis is more than means and standard deviations. This ebook is a case study of how you can push R into new territory to analyze online real-world data. The authors scrape …
What value does semantic data modeling offer? As an information architect or data science professional, let’s say you have an abundance of the right data and the technology to …
Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today's data science applications. With this practical …
Get a solid grounding in Apache Oozie, the workflow scheduler system for managing Hadoop jobs. With this hands-on guide, two experienced Hadoop practitioners walk you through the …
Because databases often stay in production for decades, careful design is critical to making the database serve the needs of your users over years, and to avoid subtle errors or …
Views are virtual tables. That means they should be updatable, just as "real" or base tables are. In fact, view updatability isn't just desirable, it's crucial, for practical …