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 Data Modeling with NoSQL Database: 3rd Edition by Ajit Singh English | November 6, 2022 | ISBN: N/A | ASIN: B0BLLPHKPF | 104 pages | EPUB | 3.51 Mb ● An important step in database implementation is the data modeling, because it facilitates the understanding of the project through key features that can prevent programming and operation errors.  Data Marketing with BigQuery: The Non-Technical Guide to Analysis: From Excel to SQL: How to Master GA4, Escape Spreadsheet Hell, and Analyze Millions of Data Rows in Seconds English | 18 Jan. 2026 | ASIN: B0GHHMCYNC | 81 pages | Epub | 348.07 KB Is your spreadsheet crashing every time you open a monthly report? The era of the simple spreadsheet is over. Modern Digital Marketing generates millions of data points, and professionals who don't master SQL and Big Data risk becoming obsolete. But you don't need to be a software engineer to level up. This book is the survival guide for marketing analysts, media buyers, and growth hackers who need speed and scalability . Written in plain, non-technical language, it cuts through the jargon and focuses on what matters: business intelligence. What you will learn: How to connect Google Analytics 4 (GA4) to BigQuery for free. How to replace VLOOKUP with simple yet powerful SQL queries. How to "unnest" complex GA4 data structures with confidence. How to build automated, real-time dashboards in Looker Studio . Break free from the 1-million-row limit. Transform your career and become a full-stack Data Analyst today.  Data Lineage for AI: AI Data, Privacy & Transparency Series, #3 English | Jan 8, 2026 | ISBN: 9798232905057 | 197 pages | EPUB (True) | 143.08 KB As artificial intelligence systems increasingly rely on large, complex, and externally sourced datasets, organizations are under growing pressure to prove where training data originated, how it was transformed, and whether it was used appropriately. Without defensible data lineage, AI systems become difficult to audit, explain, or regulate.  Data Lake Integration with Emerging Technologies by Ajit Singh English | August 22, 2025 | ISBN: N/A | ASIN: B0FNK1VTQK | 294 pages | EPUB | 1.06 Mb A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. But a lake, if left unattended, can quickly turn into a swamp-a chaotic and unusable mess of data. The true power of a data lake is unlocked only when it is integrated with powerful, transformative technologies that can navigate its depths, process its contents, and extract profound insights. This book, "Data Lake Integration with Emerging Technologies," is born from the necessity to bridge this critical gap.  Data Envelopment Analysis: An intuitive introduction to relative efficiency analysis English | 13 Jan. 2026 | ASIN: B0GGGLHNFN | Pages not found | Epub | 426.98 KB Efficiency is one of the most widely used - and most misunderstood - concepts in performance analysis. Most methods reduce efficiency to a single indicator, a ranking, or an average. Data Envelopment Analysis (DEA) takes a fundamentally different approach. This book offers a clear, intuitive, and conceptually rigorous introduction to DEA , designed for readers who want to understand efficiency - not just calculate it. Written by a researcher with extensive academic and applied experience in DEA, this book transforms a complex quantitative method into an accessible framework for reasoning about performance, comparison, and improvement. Rather than focusing on formulas or software, the book builds understanding step by step: What efficiency really means in real-world settings Why simple indicators and rankings often fail How relative efficiency differs from absolute performance What the efficient frontier represents - and what it does not Why flexibility in weights is essential for fairness How scale, orientation, benchmarks, and slacks shape interpretation When DEA should be used - and when it should not Throughout the book, efficiency is treated not as a judgment, but as a learning opportunity . DEA is presented as a tool for: benchmarking rather than ranking learning rather than labeling improvement rather than punishment The result is a book that bridges the gap between theory and practice, making DEA accessible to: undergraduate and graduate students researchers entering efficiency analysis professionals working with performance evaluation, benchmarking, or policy analysis If you have ever run a DEA model without fully trusting the results - or avoided the method because it seemed too technical - this book was written for you. Efficiency is not about being the best. It is about being the best possible, given the circumstances.  Data Engineering with AWS: A practical guide to building scalable and secure enterprise data platforms (English Edition) by Sanjiv Kumar Jha English | August 28, 2025 | ISBN: 9365890969 | 446 pages | MOBI | 4.31 Mb Data engineering and AWS form the backbone of modern enterprise data architecture, enabling organizations to harness the exponential growth of data for competitive advantage. As businesses generate petabytes of information daily, the ability to build scalable, secure, and cost-effective data platforms has become critical for survival in today's data-driven economy.  Data Engineering for Machine Learning: Designing Robust Pipelines and Workflows by Nicholas Hopkins English | June 14, 2025 | ISBN: N/A | ASIN: B0FD8YCVM8 | 194 pages | EPUB | 0.28 Mb Data Engineering for Machine Learning: Designing Robust Pipelines and Workflows  Data Engineering for Cybersecurity: Designing Scalable Pipelines, Schemas, and Analytics to Power Modern Threat Hunting and Incident Response by John M. Wade English | December 20, 2025 | ISBN: B0G9T5XFMS | 147 pages | EPUB | 2.80 Mb Master the Data Behind the Defense  Data Clustering with Python: From Theory to Implementation (Chapman & Hall/CRC The Python Series) by Guojun Gan English | September 14, 2025 | ISBN: 1032971568 | 248 pages | MOBI | 3.97 Mb Data clustering, an interdisciplinary field with diverse applications, has gained increasing popularity since its origins in the 1950s. Over the past six decades, researchers from various fields have proposed numerous clustering algorithms. In 2011, I wrote a book on implementing clustering algorithms in C++ using object-oriented programming. While C++ offers efficiency, its steep learning curve makes it less ideal for rapid prototyping. Since then, Python has surged in popularity, becoming the most widely used programming language since 2022. Its simplicity and extensive scientific libraries make it an excellent choice for implementing clustering algorithms.  Data Analytics using Machine Learning Techniques on Cloud Platforms by Seema Rawat, Neelu Jyothi Ahuja, Avita Katal English | September 22, 2025 | ISBN: 1032491469 | 204 pages | MOBI | 3.54 Mb Data Analytics using Machine Learning Techniques on Cloud Platforms examines how machine learning (ML) and cloud computing combine to drive data-driven decision-making across industries. Covering ML techniques, loud-based analytics tools and security concerns, this book provides theoretical foundations and real-world applications in fields like healthcare, logistics and e-commerce. It also addresses security challenges, privacy concerns and compliance frameworks, ensuring a comprehensive understanding of cloud-based analytics. |
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