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Databricks Data Intelligence Platform: Unlocking the GenAI Revolution by Nikhil Gupta, Jason Yip English | October 13, 2024 | ISBN: 8868804433 | 492 pages | MOBI | 17 Mb This book is your comprehensive guide to building robust Generative AI solutions using the Databricks Data Intelligence Platform. Databricks is the fastest-growing data platform offering unified analytics and AI capabilities within a single governance framework, enabling organizations to streamline their data processing workflows, from ingestion to visualization. Additionally, Databricks provides features to train a high-quality large language model (LLM), whether you are looking for Retrieval-Augmented Generation (RAG) or fine-tuning. Databricks offers a scalable and efficient solution for processing large volumes of both structured and unstructured data, facilitating advanced analytics, machine learning, and real-time processing. In today's GenAI world, Databricks plays a crucial role in empowering organizations to extract value from their data effectively, driving innovation and gaining a competitive edge in the digital age. This book will not only help you master the Data Intelligence Platform but also help power your enterprise to the next level with a bespoke LLM unique to your organization. Beginning with foundational principles, the book starts with a platform overview and explores features and best practices for ingestion, transformation, and storage with Delta Lake. Advanced topics include leveraging Databricks SQL for querying and visualizing large datasets, ensuring data governance and security with Unity Catalog, and deploying machine learning and LLMs using Databricks MLflow for GenAI. Through practical examples, insights, and best practices, this book equips solution architects and data engineers with the knowledge to design and implement scalable data solutions, making it an indispensable resource for modern enterprises. Whether you are new to Databricks and trying to learn a new platform, a seasoned practitioner building data pipelines, data science models, or GenAI applications, or even an executive who wants to communicate the value of Databricks to customers, this book is for you. With its extensive feature and best practice deep dives, it also serves as an excellent reference guide if you are preparing for Databricks certification exams. What You Will Learn Foundational principles of Lakehouse architectureKey features including Unity Catalog, Databricks SQL (DBSQL), and Delta Live TablesDatabricks Data Intelligence Platform and key functionalitiesBuilding and deploying GenAI Applications from data ingestion to model servingDatabricks pricing, platform security, DBRX, and many more topics Who This Book Is For Solution architects, data engineers, data scientists, Databricks practitioners, and anyone who wants to deploy their GenAI solutions with the Data Intelligence Platform. This is also a handbook for senior execs who need to communicate the value of Databricks to customers. People who are new to the Databricks Platform and want comprehensive insights will find the book accessible. Download Links RapidGator https://rg.to/file/4b0d9483b025fba936ba4e4cc5b6d3b0/kgopx.7z.html TakeFile https://takefile.link/4j4tj1ujbn43/kgopx.7z.html Fileaxa https://fileaxa.com/0hmge5swy89v/kgopx.7z Fikper https://fikper.com/gEVSmI2ZPD/kgopx.7z.html

Databricks Certified Data Engineer Associate Study Guide: In-Depth Guidance and Practice by Derar Alhussein English | April 1st, 2025 | ISBN: 1098166833 | 408 pages | True EPUB (Retail Copy) | 30.09 MB Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform. In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests. Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks! You'll learn how to: * Use the Databricks Platform and Delta Lake effectively * Perform advanced ETL tasks using Apache Spark SQL * Design multi-hop architecture to process data incrementally * Build production pipelines using Delta Live Tables and Databricks Jobs * Implement data governance using Databricks SQL and Unity Catalog Derar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications. Download Links RapidGator https://rg.to/file/ad1d08fff3fc93b963d9a11c487cbb2e/77ub6.7z.html TakeFile https://takefile.link/kdvmehbudc3c/77ub6.7z.html Fileaxa https://fileaxa.com/o37i9pe82slm/77ub6.7z Fikper https://fikper.com/oYolJt2cAu/77ub6.7z.html

Databricks Certified Data Engineer Associate Study Guide English | 2025 | ISBN: 1098166833 | 495 Pages | EPUB | 32 MB Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform. Download Links RapidGator https://rg.to/file/fb230381e5dc93ecabeb209d824cbe46/nqtec.7z.html TakeFile https://takefile.link/xppyi5rjbo3i/nqtec.7z.html Fileaxa https://fileaxa.com/xuxii7phqpnx/nqtec.7z Fikper https://fikper.com/AcaF864S97/nqtec.7z.html

Database Design with SQL: Building Fast and Reliable Systems by Robert Johnson English | October 26, 2024 | ISBN: N/A | ASIN: B0DL3ZZC2S | 425 pages | PDF | 1.60 Mb "Database Design with SQL: Building Fast and Reliable Systems" is an essential resource for beginners eager to master the fundamentals of database management and SQL. This comprehensive guide demystifies the core principles of database systems, providing readers with the knowledge to design efficient data architectures and execute complex SQL operations. Covering everything from basic data structures to advanced query optimization, the book equips learners with the crucial skills needed to build and manipulate robust databases that meet modern demands. The book delves into the intricacies of relational databases and normalization, offering practical insights into data modeling and schema design. Readers will explore the power of SQL in both data retrieval and manipulation, progressing through foundational commands to sophisticated techniques like dynamic SQL and window functions. Additionally, the text addresses critical aspects of database security, transactions, and concurrency control, ensuring that systems remain resilient and secure in multi-user environments. Beyond relational databases, "Database Design with SQL" introduces the versatile world of NoSQL and its role in big data, enabling learners to handle diverse data types and high-volume datasets. Through real-world case studies and best practices for database administration, this guide offers valuable strategies for maintaining performance and reliability. Whether you are embarking on a career in database management or seeking to enhance your technical expertise, this book is your gateway to mastering database design and SQL with confidence. Download Links RapidGator https://rg.to/file/face99fb95f63a0ebe3cd9bb715f73c3/qy8ah.7z.html TakeFile https://takefile.link/73tc0ie2k51d/qy8ah.7z.html Fileaxa https://fileaxa.com/r2lavg01oc9o/qy8ah.7z Fikper https://fikper.com/yNrCBGfhHK/qy8ah.7z.html

Data-Driven Talent Management: Using Analytics to Improve Employee Experience by Kristin Saling English | August 27, 2024 | ISBN: 139861629X | 248 pages | MOBI | 1.85 Mb How can I use insights from people data to develop an inclusive, engaged, high-performing workforce? What data is available and how do I collect it ethically? Data-Driven Talent Management is a practical guide for HR professionals which answers these questions. It outlines effective data collection and analysis methods as well as showing how to develop metrics and key performance indicators to support employee experience. It also provides guidance on how to build a comprehensive talent database by understanding different employee experiences, attributes, skills and journeys. In addition, there is also essential advice on how to leverage data to improve motivation and employee engagement, use data to assess different thought and work styles in the workforce and use the results to build a diverse and inclusive organization that allows all employees and the business to thrive. Full of tools, tips and frameworks and written by a professional who is implementing a data-driven approach to talent management for the US Army, the world's largest employer, this is essential reading for all mid-level and senior HR practitioners. Download Links RapidGator https://rg.to/file/2fe118ee079cb988354646b385054b8a/j4tbg.7z.html TakeFile https://takefile.link/cmsm109c2a2i/j4tbg.7z.html Fileaxa https://fileaxa.com/n34ll05efrfh/j4tbg.7z Fikper https://fikper.com/HlGFYVUVXk/j4tbg.7z.html

Data-Centric Machine Learning with Python: The ultimate guide to engineering and deploying high-quality models based on good data by Jonas Christensen, Nakul Bajaj, Manmohan Gosada English | February 29, 2024 | ISBN: 1804618128 | 378 pages | PDF | 6.01 Mb Join the data-centric revolution and master the concepts, techniques, and algorithms shaping the future of AI and ML development, using Python Key FeaturesGrasp the principles of data centricity and apply them to real-world scenariosGain experience with quality data collection, labeling, and synthetic data creation using PythonDevelop essential skills for building reliable, responsible, and ethical machine learning solutionsPurchase of the print or Kindle book includes a free PDF eBookBook Description In the rapidly advancing data-driven world where data quality is pivotal to the success of machine learning and artificial intelligence projects, this critically timed guide provides a rare, end-to-end overview of data-centric machine learning (DCML), along with hands-on applications of technical and non-technical approaches to generating deeper and more accurate datasets. This book will help you understand what data-centric ML/AI is and how it can help you to realize the potential of 'small data'. Delving into the building blocks of data-centric ML/AI, you'll explore the human aspects of data labeling, tackle ambiguity in labeling, and understand the role of synthetic data. From strategies to improve data collection to techniques for refining and augmenting datasets, you'll learn everything you need to elevate your data-centric practices. Through applied examples and insights for overcoming challenges, you'll get a roadmap for implementing data-centric ML/AI in diverse applications in Python. By the end of this book, you'll have developed a profound understanding of data-centric ML/AI and the proficiency to seamlessly integrate common data-centric approaches in the model development lifecycle to unlock the full potential of your machine learning projects by prioritizing data quality and reliability. What you will learnUnderstand the impact of input data quality compared to model selection and tuningRecognize the crucial role of subject-matter experts in effective model developmentImplement data cleaning, labeling, and augmentation best practicesExplore common synthetic data generation techniques and their applicationsApply synthetic data generation techniques using common Python packagesDetect and mitigate bias in a dataset using best-practice techniquesUnderstand the importance of reliability, responsibility, and ethical considerations in ML/AIWho this book is for This book is for data science professionals and machine learning enthusiasts looking to understand the concept of data-centricity, its benefits over a model-centric approach, and the practical application of a best-practice data-centric approach in their work. This book is also for other data professionals and senior leaders who want to explore the tools and techniques to improve data quality and create opportunities for small data ML/AI in their organizations. Table of ContentsExploring Data-Centric Machine LearningFrom Model-Centric to Data-Centric - ML's EvolutionPrinciples of Data-Centric MLData Labeling Is a Collaborative ProcessTechniques for Data CleaningTechniques for Programmatic Labeling in Machine LearningUsing Synthetic Data in Data-Centric Machine LearningTechniques for Identifying and Removing BiasDealing with Edge Cases and Rare Events in Machine LearningKick-Starting Your Journey in Data-Centric Machine Learning Download Links RapidGator https://rg.to/file/b36ca4b45c8aadafecb581209ba8abe5/vs51h.7z.html TakeFile https://takefile.link/01xtqdu9m0n9/vs51h.7z.html Fileaxa https://fileaxa.com/bjv3hgegxf5t/vs51h.7z Fikper https://fikper.com/nfYNw3MP7x/vs51h.7z.html

Data Structures and Algorithms with the C++ STL: A guide for modern C++ practitioners by John Farrier English | February 29, 2024 | ISBN: 1835468551 | 458 pages | EPUB | 4.91 Mb Explore the C++ 23 STL with practical guidance on vectors, algorithms, and custom types for intermediate developers, enriched by real-world examples.Key FeaturesMaster the std:: vector and understand why it should be your default container of choiceUnderstand each STL algorithm and its practical applicationsGain insights into advanced topics such as exception guarantees and thread safetyPurchase of the print or Kindle book includes a free PDF eBookBook Description While the Standard Template Library (STL) offers a rich set of tools for data structures and algorithms, navigating its intricacies can be daunting for intermediate C++ developers without expert guidance. This book offers a thorough exploration of the STL's components, covering fundamental data structures, advanced algorithms, and concurrency features. Starting with an in-depth analysis of the std:: vector, this book highlights its pivotal role in the STL, progressing toward building your proficiency in utilizing vectors, managing memory, and leveraging iterators. The book then advances to STL's data structures, including sequence containers, associative containers, and unordered containers, simplifying the concepts of container adaptors and views to enhance your knowledge of modern STL programming. Shifting the focus to STL algorithms, you'll get to grips with sorting, searching, and transformations and develop the skills to implement and modify algorithms with best practices. Advanced sections cover extending the STL with custom types and algorithms, as well as concurrency features, exception safety, and parallel algorithms. By the end of this book, you'll have transformed into a proficient STL practitioner ready to tackle real-world challenges and build efficient and scalable C++ applications.What you will learnStreamline data handling using the std:: vectorMaster advanced usage of STL iteratorsOptimize memory in STL containersImplement custom STL allocatorsApply sorting and searching with STL algorithmsCraft STL-compatible custom typesManage concurrency and ensure thread safety in STLHarness the power of parallel algorithms in STLWho this book is for This book is for intermediate-level C++ developers looking to enhance their software development skills. Familiarity with basic C++ syntax and object-oriented programming (OOP) as well as some exposure to data structures and algorithms is assumed. Tailored to software engineers, computer science students, and hobbyist programmers, this book delves into C++ STL for practical application, performance enhancement, and efficient coding practices.Table of ContentsThe Basics of std:: vectorMastering Iterators with std:: vectorMastering Memory and Allocators with std:: vectorMastering Algorithms with std:: vectorMaking a Case for std:: vectorAdvanced Sequence Container UsageAdvanced Ordered Associative Container UsageAdvanced Unordered Associative Container UsageAdvanced Container Adaptor UsageAdvanced Container View UsageFundamental Algorithms and SearchingManipulation and TransformationNumeric and Range-Based OperationsPermutations, Partitions, and HeapsSTL with RangesCreating STL-Types ContainersCreating STL-Compatible AlgorithmsType Traits and PoliciesException SafetyThread Safety and Concurrency with the STLSTL Interaction with Concepts and CoroutinesParallel Algorithms with the STL Download Links RapidGator https://rg.to/file/165d9e73f1d9701990b71c2dc9766327/747jn.7z.html TakeFile https://takefile.link/5ijj2txmyln0/747jn.7z.html Fileaxa https://fileaxa.com/psag42umy2bb/747jn.7z Fikper https://fikper.com/df12vLv1NG/747jn.7z.html

Data Structures and Algorithms with Python English | 2025 | ASIN : B0DXV3LCCC | 278 Pages | PDF EPUB | 9 MB "Dive into the Heart of Pythonic Algorithms and Data Structures" offers a comprehensive guide designed to empower both beginners and seasoned developers. Whether you're mastering the foundations of computer science or enhancing your problem-solving skills, this book provides a roadmap through the intricacies of efficient data organization and algorithmic prowess. Download Links RapidGator https://rg.to/file/68d78716be87e05a5ba16ee0c7656994/acafm.7z.html TakeFile https://takefile.link/bdjc8sx5w7mo/acafm.7z.html Fileaxa https://fileaxa.com/suupowdfgo22/acafm.7z Fikper https://fikper.com/oiRfM2gDTN/acafm.7z.html

Data Science Mastery: From Beginner to Expert in Big Data Analytics by Kameron Hussain English | January 17, 2025 | ISBN: 8230236437 | 112 Pages | True epub | 0,18 MB Unlock the secrets of data science with Data Science Mastery: From Beginner to Expert in Big Data Analytics**! This comprehensive guide takes you on a transformative journey, whether you're a complete novice or an experienced professional looking to sharpen your skills. Learn how to harness the power of data to make informed decisions, create predictive models, and drive innovation in any field.** This book provides a step-by-step approach, starting with the basics of data science, including statistical concepts, data collection, and cleaning techniques. Progress into advanced topics such as machine learning algorithms, deep learning, and big data technologies like Hadoop and Spark. Each chapter includes practical examples and hands-on exercises to solidify your understanding. Key features include: Clear Explanations: Understand complex topics like artificial intelligence and data engineering with ease. Practical Applications: Learn how to analyze real-world datasets and develop impactful data visualizations. Tools and Languages: Gain expertise in Python, R, SQL, and other essential tools for data science. Advanced Techniques: Dive into neural networks, natural language processing, and big data analytics to stay ahead in the competitive field of data science. Career Insights: Discover tips on building a strong data science portfolio, acing interviews, and staying updated with the latest trends. Whether you're preparing for a career in data science, advancing your current skills, or simply curious about the field, this book will equip you with everything you need to succeed. Designed for learners of all levels, Data Science Mastery is your ultimate guide to mastering the art of big data analytics. Embrace the future of data-driven success and become an expert in data science today! eBook Details: Kameron Hussain 112 Pages 2 - 3 Hours to read 35k Total words Release Date: January 17, 2025 ISBN-13: 9798230236436 ISBN-10: 8230236437 Language: English Format: epub ✅File Size: 0,18 MB Download Links RapidGator https://rg.to/file/5e4dcc54d1326c8317d324fee4b6b78d/azdl2.7z.html TakeFile https://takefile.link/y5tantvcv27g/azdl2.7z.html Fileaxa https://fileaxa.com/1nc10bqxowre/azdl2.7z Fikper https://fikper.com/pYjO8JAW4D/azdl2.7z.html

Data Science in Engineering Vol. 10 English | 2025 | ISBN: 303168141X | 141 Pages | PDF (True) | 18 MB Data Science in Engineering, Volume 10: Proceedings of the 42nd IMAC, A Conference and Exposition on Structural Dynamics, 2024, the tenth volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Data Science in Engineering, including papers on: Download Links RapidGator https://rg.to/file/268793931948f2411209c9184eeccdbb/f8jt2.7z.html TakeFile https://takefile.link/fanqxqb5mbon/f8jt2.7z.html Fileaxa https://fileaxa.com/vhjop9ad8oc3/f8jt2.7z Fikper https://fikper.com/1mZBzGgZUX/f8jt2.7z.html

Data Science from Scratch: A Complete Beginner's Guide to Mastering Analytics, Machine Learning, and Real-World Applications English | 2025 | ASIN : B0DXBYJ24Z | 97 Pages | EPUB | 1.3 MB Are you ready to dive into the world of data science but don't know where to start? Data Science from Scratch is your ultimate beginner-friendly guide to building a strong foundation in analytics, machine learning, and real-world applications-without needing a PhD in math or programming. Download Links RapidGator https://rg.to/file/2fb0ff1c5997c14f1eecb13cf9527113/kcbwv.7z.html TakeFile https://takefile.link/r3zt9p13wj2a/kcbwv.7z.html Fileaxa https://fileaxa.com/7vv2kvkydxg8/kcbwv.7z Fikper https://fikper.com/Q97nBG8Pmv/kcbwv.7z.html

Data Science for Political Campaigns: Winning with Analytics. Python, Excel & R: Reactive Publishing by Hayden Van Der Post, Reactive Publishing English | January 21, 2025 | ISBN: N/A | ASIN: B0DTN6H25X | 390 pages | EPUB | 1.29 Mb Reactive Publishing Revolutionize Political Campaigning with the Power of Data Science In the modern political arena, analytics isn't optional-it's the game changer. Data Science for Political Campaigns: Winning with Analytics is your essential guide to leveraging data science techniques to craft smarter, more targeted, and more effective campaigns. This book provides a practical roadmap for political strategists, campaign managers, and data professionals looking to harness the full potential of data-driven decision-making. From voter segmentation to real-time performance tracking, you'll learn how to apply cutting-edge analytics to every stage of the campaign process. What You'll Discover:Voter Segmentation: Use clustering and classification to identify key voter groups and their preferences.Predictive Analytics: Forecast voter turnout, election outcomes, and donation trends using machine learning models.Targeted Outreach: Optimize campaign messages and advertising with personalized insights.Social Media Analytics: Monitor and influence public sentiment through advanced sentiment analysis.Geo-Spatial Insights: Leverage geospatial data to optimize grassroots efforts and identify high-priority regions.Real-Time Dashboards: Build and deploy live campaign performance trackers using Python, R, or Tableau.Whether you're running a local city council campaign or managing a national election, this book offers actionable tools and strategies to take your campaign to the next level. With real-world examples, code snippets, and easy-to-follow tutorials, Data Science for Political Campaigns empowers you to win with data. Take the guesswork out of politics and start running campaigns that win. Download Links RapidGator https://rg.to/file/aa6b227872f3911bd572493bc49b1c12/rr2bn.7z.html TakeFile https://takefile.link/n6ep8cxos1eu/rr2bn.7z.html Fileaxa https://fileaxa.com/ksf7p80eq1oc/rr2bn.7z Fikper https://fikper.com/jCwRADeyF9/rr2bn.7z.html

Data Science e Machine Learning - Seconda Edizione by Michele di Nuzzo Italian | January 6, 2025 | ISBN: 0008675945 | 522 Pages | True epub | 6,61 MB In un'era in cui i dati sono considerati il nuovo petrolio, capire come estrarre valore da essi è diventato essenziale per qualsiasi professionista o azienda che voglia rimanere competitiva. "Data Science e Machine Learning" di Michele di Nuzzo è la guida definitiva per chi desidera immergersi nel mondo della scienza dei dati, apprendere le tecniche di machine learning più avanzate e scoprire come applicarle ai problemi reali. Contenuto Questo libro offre: Una panoramica dettagliata della scienza dei dati, delle sue origini e della sua evoluzione. I fondamenti matematici e gli strumenti statistici per l'analisi e la modellazione dei dati Elementi di statistica decrittiva, inferenziale e teoria della probabilità Fondamenti di Machine Learning: spiegazioni chiare e concise dei prin[beeep]li algoritmi di apprendimento automatico, dai più semplici ai più complessi. Tecniche per la modellazione e la validazione dei modelli di machine learning. Esempi ed esercizi pratici per mettere subito in pratica le competenze acquisite. Una guida completa sugli strumenti più utilizzati nel campo, da Python, NumPy, Pandas, MatDescriptionlib, Scikit-learn e altre librerie essenziali. Capitoli dedicati a tecniche avanzate come l'apprendimento non supervisionato, l'apprendimento semi-supervisionato e i metodi ensamble. A chi è rivolto questo libro Questo libro è rivolto a chiunque voglia imparare a manipolare ed analizzare i dati traendo da questi nuova conoscenza. Se sei un manager IT o un analista che vuole entrare nel mondo della Data Science e dei Big Data, se sei uno sviluppatore che vuole conoscere le nuove tendenze nel campo dell'apprendimento automatico o sei semplicemente curioso di conoscere questo mondo, allora questo libro è per te. eBook Details: Michele di Nuzzo 522 Pages 10 - 11 Hours to read 132k Total words Release Date: January 6, 2025 ISBN-13: 1230008675941 ISBN-10: 0008675945 Language: Italian Format: epub ✅File Size: 6,61 MB Download Links RapidGator https://rg.to/file/7b568c2ffe0bc27f8453a1cff1d132ca/vil66.7z.html TakeFile https://takefile.link/ivmesgw8l0ya/vil66.7z.html Fileaxa https://fileaxa.com/z0zzzgdvjxd9/vil66.7z Fikper https://fikper.com/1aOPX7f2Sn/vil66.7z.html

Data Science and Network Engineering: Proceedings ICDSNE 2024 English | 2025 | ISBN: 9819783356 | 654 Pages | PDF EPUB (True) | 70 MB This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2024) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 12-13, 2024. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering. Download Links RapidGator https://rg.to/file/f7bdc3fa3038fb23c53362d41df407b0/v9tk2.7z.html TakeFile https://takefile.link/5canjitnszec/v9tk2.7z.html Fileaxa https://fileaxa.com/z68zho5yf3ng/v9tk2.7z Fikper https://fikper.com/ZTdE1fqSHf/v9tk2.7z.html

Data Science and Applications for Modern Power Systems (Power Electronics and Power Systems) by Le Xie, Yang Weng, Ram Rajagopal English | June 21, 2023 | ISBN: 3031290992 | 451 pages | MOBI | 41 Mb This book offers a comprehensive collection of research articles that utilize data―in particular large data sets―in modern power systems operation and planning. As the power industry moves towards actively utilizing distributed resources with advanced technologies and incentives, it is becoming increasingly important to benefit from the available heterogeneous data sets for improved decision-making. The authors present a first-of-its-kind comprehensive review of big data opportunities and challenges in the smart grid industry. This book provides succinct and useful theory, practical algorithms, and case studies to improve power grid operations and planning utilizing big data, making it a useful graduate-level reference for students, faculty, and practitioners on the future grid. Download Links RapidGator https://rg.to/file/ea828b7f9b70e997ba4430ad8eb47112/xtgrp.7z.html TakeFile https://takefile.link/ao4574bopnrn/xtgrp.7z.html Fileaxa https://fileaxa.com/l4s6hhzelpcc/xtgrp.7z Fikper https://fikper.com/miZXjCE8uP/xtgrp.7z.html

Data Migration for SAP: SAP S/4HANA and Cloud Solutions (SAP PRESS) by Frank Finkbohner, Martina Höft, Michael Roth English | May 29, 2024 | ISBN: 1493225227 | 600 pages | MOBI | 33 Mb Whether you're moving to the cloud, migrating to SAP S/4HANA, or replacing a legacy system, get the data migration guidance you need in this comprehensive guide. Evaluate your landscape options and plan your strategy; then walk through the migration processes for SAP S/4HANA, SAP SuccessFactors, SAP Ariba, and SAP Business ByDesign. Master built-in tools and templates, IDoc and ALE distribution models, batch input, Cloud Integration from SAP Integration Suite, and more!Plan and execute SAP data migration without programmingLearn to migrate data to SAP S/4HANA, SAP SuccessFactors, SAP Ariba, and SAP Business ByDesignExplore migration tools including Cloud Integration, SAP Legacy System Migration Workbench, batch input, IDocs, and ALE Data Migration Basics Review the technical fundamentals of data migration in an easy-to-understand way. Compare migration strategies and scenarios-including greenfield, brownfield, and hybrid implementations-and learn how to plan your migration project efficiently from start to finish. SAP Solution Migration Follow step-by-step instructions to migrate data to SAP systems. See how the migration cockpit and the migration object modeler ease the transition to SAP S/4HANA, and get expert guidance for migrating to cloud-based solutions like SAP SuccessFactors, SAP Ariba, and SAP Business ByDesign. Migration Approaches Learn to use classic migration methods, including IDoc and ALE distribution models, batch input, and database migration. Convert data types and data constellations without the need for programming. Use SAP Legacy System Migration Workbench and Cloud Integration to seamlessly transition data between different systems.PlanningSAP S/4HANASAP S/4HANA CloudSAP SuccesFactorsSAP AribaSAP Business ByDesignSAP Legacy System Migration WorkbenchSAP S/4HANA migration cockpitCloud IntegrationSAP S/4HANA migration object modelerBatch inputIDoc and ALE distribution models Download Links RapidGator https://rg.to/file/2f7d6dd1ee78ed254b18b275fb5569f2/d1od2.7z.html TakeFile https://takefile.link/a7uwg8ardebj/d1od2.7z.html Fileaxa https://fileaxa.com/flx8tojbdh50/d1od2.7z Fikper https://fikper.com/hq3MaCrCs7/d1od2.7z.html

Data Independence: Reclaiming Privacy in an Era of Evolving Tech by Wes Chaar English | September 24, 2024 | ISBN: 1642259756 | 176 pages | PDF | 3.89 Mb In the digital age, our personal data has become a valuable commodity, sought after by corporations, organizations, and governments alike. Data Independence: Reclaiming Privacy in an Era of Evolving Tech is a groundbreaking book by data scientist Wes Chaar that exposes the hidden world of the data economy and offers a revolutionary solution to reclaim our data rights. With over twenty years of experience in the data space, Chaar reveals some of the hidden techniques used to collect, analyze, and monetize our personal information without our complete knowledge or understanding. From our daily activities, online behavior and purchases, and social media interactions to location tracking and biometric data, every aspect of our lives is being monitored and compiled into a digital dossier, which provides significant insights into an individual and monetization opportunities for corporations. Data Independence is more than just a revelation―it's a revolution to reclaim your rights. Chaar introduces the Personal Data Vault Key, a tool concept that puts individuals in control of their data. By leveraging the principles of data consent, control, and currency, everyone is in charge of their data. This creates transparency, accountability, protection, equality, and respect between you and the entities you allow to use your data assets on your terms. The Personal Data Vault Key empowers users to decide who accesses their data, how it's used, and even how to monetize it. Through compelling case studies, expert insights, and practical guidance, Data Independence demystifies the complex world of data privacy and provides readers with the knowledge and tools they need to protect their data power. Chaar's engaging and accessible writing style makes even the most technical concepts easy to understand, while his passionate advocacy for privacy rights is both inspiring and empowering. Whether you're concerned about your offline and online privacy, curious about the inner workings of the data economy, or seeking to leverage your personal data for your own benefit, Data Independence is an essential read. It's a call to action for a data revolution―one that puts the power back in the hands of the people. Join Wes Chaar on this transformative journey and discover how to unlock the power of personal data control. Your data future starts here. Download Links RapidGator https://rg.to/file/6f08d77cff6cbb2af5055e3eb865f042/4gpfg.7z.html TakeFile https://takefile.link/za8obpqvo51z/4gpfg.7z.html Fileaxa https://fileaxa.com/nnopir85lhp9/4gpfg.7z Fikper https://fikper.com/ZuGiCL8dit/4gpfg.7z.html

Data Governance with Unity Catalog on Databricks English | 2025 | ISBN: 9781098179625 | 86 Pages | EPUB | 9 MB Organizations collecting and using personal data must now heed a growing body of regulations, and the penalties for noncompliance are stiff. The ubiquity of the cloud and the advent of generative AI have only made it more crucial to govern data appropriately. Thousands of companies have turned to Databricks Unity Catalog to simplify data governance and manage their data and AI assets more effectively. This practical guide helps you do the same. Download Links RapidGator https://rg.to/file/698c233ec292d6733fca5f209a163bba/v6zhi.7z.html TakeFile https://takefile.link/gd6hc9f1xem2/v6zhi.7z.html Fileaxa https://fileaxa.com/0agw1bplmb3b/v6zhi.7z Fikper https://fikper.com/lSHiJJlPM7/v6zhi.7z.html

Joseph Lee, "Data Governance in AI, FinTech and LegalTech: Law and Regulation in the Financial Sector" English | ISBN: 1800379943 | 2022 | 320 pages | PDF | 1273 KB Advocating for more standardised data governance practices and promoting the digital economy, Data Governance in AI, FinTech and LegalTech investigates the rationale, legal base and tools of data governance in the financial sector. This timely book makes a significant contribution to the debate around how rapidly-evolving digital finance practices should be regulated. Contributions from leading researchers examine a range of financial services, offering a comprehensive assessment of the available tools for constructing multi-layered matrix systems for data governance in the financial services sector. Chapters explore data governance in the cryptocurrency market, crypto-asset providers, legal services for mergers and acquisitions, consumer insurance, consumer finance, digital platform services, securities exchanges and the green bond market. The book serves to define the legal contours of data governance, taking account of the influence of shifting business models, the views of multiple stakeholders and emerging issues surrounding data protection, privacy and cybersecurity. Read more Download Links RapidGator https://rg.to/file/9f3343bb2277d3fd57f3fee075100131/hn8xe.7z.html TakeFile https://takefile.link/cfaoqyx5rffg/hn8xe.7z.html Fileaxa https://fileaxa.com/0egsqy3prpl1/hn8xe.7z Fikper https://fikper.com/71PsEGncbS/hn8xe.7z.html

Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud by Adi Wijaya English | April 30, 2024 | ISBN: 1835080111 | 476 pages | PDF | 45 Mb Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions Key FeaturesGet up to speed with data governance on Google CloudLearn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and DatastreamBoost your confidence by getting Google Cloud data engineering certification guidance from real exam experiencesPurchase of the print or Kindle book includes a free PDF eBookBook Description The second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering. Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You'll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you'll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets. By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices. What you will learnLoad data into BigQuery and materialize its outputFocus on data pipeline orchestration using Cloud ComposerFormulate Airflow jobs to orchestrate and automate a data warehouseEstablish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc clusterHarness Pub/Sub for messaging and ingestion for event-driven systemsApply Dataflow to conduct ETL on streaming dataImplement data governance services on Google CloudWho this book is for Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you're a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you. Table of ContentsFundamentals of Data engineering with GCPBig Data Capabilities on GCPBuilding a data warehouse in BigQueryBuild Orchestration for Batch Data Loading Using Cloud ComposerBuilding a Data Lake using DataprocProcess Streaming Data with Datastream, Pub/Sub and DataflowVisualizing Data for Making Data-Driven Decisions with Looker StudioBuild machine learning solutions on GCPUser and Project Management on GCPData Governance in GCPCost Strategy in GCPCI/CD on Google Cloud Platform for Data EngineersBoost your confidence as a Data Engineer Download Links RapidGator https://rg.to/file/9bb28192e2f806b399d6678a68863eb6/z6npc.7z.html TakeFile https://takefile.link/ooqje327smbw/z6npc.7z.html Fileaxa https://fileaxa.com/4siiotc0ekb4/z6npc.7z Fikper https://fikper.com/rOpTBc6Z4Y/z6npc.7z.html

Data Engineering with Google Cloud Platform: A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud by Adi Wijaya English | April 30, 2024 | ISBN: 1835080111 | 476 pages | EPUB | 21 Mb Become a successful data engineer by building and deploying your own data pipelines on Google Cloud, including making key architectural decisions Key FeaturesGet up to speed with data governance on Google CloudLearn how to use various Google Cloud products like Dataform, DLP, Dataplex, Dataproc Serverless, and DatastreamBoost your confidence by getting Google Cloud data engineering certification guidance from real exam experiencesPurchase of the print or Kindle book includes a free PDF eBookBook Description The second edition of Data Engineering with Google Cloud builds upon the success of the first edition by offering enhanced clarity and depth to data professionals navigating the intricate landscape of data engineering. Beyond its foundational lessons, this new edition delves into the essential realm of data governance within Google Cloud, providing you with invaluable insights into managing and optimizing data resources effectively. Written by a Data Strategic Cloud Engineer at Google, this book helps you stay ahead of the curve by guiding you through the latest technological advancements in the Google Cloud ecosystem. You'll cover essential aspects, from exploring Cloud Composer 2 to the evolution of Airflow 2.5. Additionally, you'll explore how to work with cutting-edge tools like Dataform, DLP, Dataplex, Dataproc Serverless, and Datastream to perform data governance on datasets. By the end of this book, you'll be equipped to navigate the ever-evolving world of data engineering on Google Cloud, from foundational principles to cutting-edge practices. What you will learnLoad data into BigQuery and materialize its outputFocus on data pipeline orchestration using Cloud ComposerFormulate Airflow jobs to orchestrate and automate a data warehouseEstablish a Hadoop data lake, generate ephemeral clusters, and execute jobs on the Dataproc clusterHarness Pub/Sub for messaging and ingestion for event-driven systemsApply Dataflow to conduct ETL on streaming dataImplement data governance services on Google CloudWho this book is for Data analysts, IT practitioners, software engineers, or any data enthusiasts looking to have a successful data engineering career will find this book invaluable. Additionally, experienced data professionals who want to start using Google Cloud to build data platforms will get clear insights on how to navigate the path. Whether you're a beginner who wants to explore the fundamentals or a seasoned professional seeking to learn the latest data engineering concepts, this book is for you. Table of ContentsFundamentals of Data engineering with GCPBig Data Capabilities on GCPBuilding a data warehouse in BigQueryBuild Orchestration for Batch Data Loading Using Cloud ComposerBuilding a Data Lake using DataprocProcess Streaming Data with Datastream, Pub/Sub and DataflowVisualizing Data for Making Data-Driven Decisions with Looker StudioBuild machine learning solutions on GCPUser and Project Management on GCPData Governance in GCPCost Strategy in GCPCI/CD on Google Cloud Platform for Data EngineersBoost your confidence as a Data Engineer Download Links RapidGator https://rg.to/file/91a7c707934f10881a1d9064d5d5064f/5w6h7.7z.html TakeFile https://takefile.link/0xguywlj87ny/5w6h7.7z.html Fileaxa https://fileaxa.com/vmpcxsgx7br5/5w6h7.7z Fikper https://fikper.com/JkMcEYF7P0/5w6h7.7z.html

Data Architectures by Prabhat Kumar English | December 28, 2024 | ISBN: 0008653496 | 161 Pages | True epub | 0,22 MB In the rapidly evolving landscape of modern technology, data has emerged as one of the most valuable assets for businesses, governments, and individuals alike. Every decision made, every process optimized, and every innovation generated is underpinned by data. From large enterprises to startups, from healthcare to finance, data drives insights, powers automation, and fuels machine learning and artificial intelligence. But despite its vast potential, data can be overwhelming-unstructured, inconsistent, and distributed across diverse systems and platforms. Data architecture, the framework for organizing, managing, and integrating this data, has never been more critical. It is the backbone that allows organizations to turn raw data into actionable insights. The design of your data architecture-whether centralized, decentralized, or hybrid-determines how efficiently and securely data flows, is stored, and is accessed within your ecosystem. The choice of architecture has significant implications for performance, scalability, data governance, and ultimately, the success of a data-driven strategy. This book aims to provide a comprehensive guide to the field of data architecture, with a focus on three major architectural paradigms: centralized, decentralized, and hybrid. These architectures represent different approaches to organizing data in a way that best supports an organization's needs, goals, and infrastructure. Understanding each of these models is essential for anyone working in data management, data engineering, or any role where data is leveraged for decision-making eBook Details: Prabhat Kumar 161 Pages 3 - 4 Hours to read 50k Total words Release Date: December 28, 2024 ISBN-13: 1230008653499 ISBN-10: 0008653496 Language: English Format: epub ✅File Size: 0,22 MB Download Links RapidGator https://rg.to/file/1a20bdc611ca56dd7bc7b8a30f9a33e9/t6q5n.7z.html TakeFile https://takefile.link/zayvn7nkuzld/t6q5n.7z.html Fileaxa https://fileaxa.com/d1yj8esrbz8f/t6q5n.7z Fikper https://fikper.com/7l7nwM41zR/t6q5n.7z.html

Data Analytics: Models and Algorithms for Intelligent Data Analysis - A Comprehensive Introduction English | 2025 | ISBN: 3658459506 | 197 Pages | PDF (True) | 6 MB This book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. The new edition integrates themes such as Word Embeddings, Transformer Models, and generative AI among the contents and offers new exercises in addition. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens. Download Links RapidGator https://rg.to/file/28e6f0fb13ff7e17fdb84197658db996/3bqwy.7z.html TakeFile https://takefile.link/cvu97mea4y9a/3bqwy.7z.html Fileaxa https://fileaxa.com/ic8xq0r7w9jm/3bqwy.7z Fikper https://fikper.com/htRdeh9NFW/3bqwy.7z.html

Data Analytics for Intelligent Systems: Techniques and Solutions (Iop Ebooks) by Sachin Taran, Chhavi Dhiman, Manjeet Kumar English | May 14, 2024 | ISBN: 0750354151 | 271 pages | AZW3 | 14 Mb This book focuses on the theory, development, novel techniques, and smart solutions in data analytics for intelligent systems that capture behaviours in complex environments. It focuses on the various advanced techniques in data analytics that can be used in different domains to solve real-time problems. Download Links RapidGator https://rg.to/file/6c229111d2b0a1fa02be569eb594ae6f/8jjcn.7z.html TakeFile https://takefile.link/tvlqkw9icm9b/8jjcn.7z.html Fileaxa https://fileaxa.com/xers469uualt/8jjcn.7z Fikper https://fikper.com/bARku6BtqB/8jjcn.7z.html

Data Analytics for Finance Using Python (Advances in Digital Technologies for Smart Applications) by Nitin Jaglal Untwal, Utku Kose English | December 30, 2024 | ISBN: 103261823X | 138 pages | MOBI | 7.02 Mb Unlock the power of data analytics in finance with this comprehensive guide. Data Analytics for Finance Using Python is your key to unlocking the secrets of the financial markets. In this book, you'll discover how to harness the latest data analytics techniques, including machine learning and inferential statistics, to make informed investment decisions and drive business success. With a focus on practical application, this book takes you on a journey from the basics of data preprocessing and visualization to advanced modeling techniques for stock price prediction. Through real-world case studies and examples, you'll learn how to:Uncover hidden patterns and trends in financial dataBuild predictive models that drive investment decisionsOptimize portfolio performance using data-driven insightsStay ahead of the competition with cutting-edge data analytics techniquesWhether you're a finance professional seeking to enhance your data analytics skills or a researcher looking to advance the field of finance through data-driven insights, this book is an essential resource. Dive into the world of data analytics in finance and discover the power to make informed decisions, drive business success, and stay ahead of the curve. This book will be helpful for students, researchers, and users of machine learning and financial tools in the disciplines of commerce, management, and economics. Download Links RapidGator https://rg.to/file/4c9ba77be18f276a5d7502f4bfb0a47b/sdjge.7z.html TakeFile https://takefile.link/7r0pnnux5rqf/sdjge.7z.html Fileaxa https://fileaxa.com/yx2sez0m17hq/sdjge.7z Fikper https://fikper.com/7RcFGamrV4/sdjge.7z.html