The "CompTIA Data+: DAO-001 Certification Guide" is your complete resource to approaching and passing the CompTIA Data+ certification exam. This book offers clear explanations, step-by-step exercises, and practical examples designed to help you master the domain concepts essential for the DAO-001 exam. Prepare confidently and expand your career opportunities in data analytics. What this Book will help me do Understand and apply the five domains covered in the DAO-001 certification exam. Learn data preparation techniques such as collection, cleaning, and wrangling. Master descriptive statistical methods and hypothesis testing to analyze data. Create insightful visualizations and professional reports for stakeholders. Grasp the fundamentals of data governance, including data quality standards. Author(s) Cameron Dodd is an experienced data analyst and educator passionate about breaking down complex concepts. With years of teaching and hands-on analytics expertise, he has developed a student-centric approach to helping professionals achieve certification and career advancement. His structured yet relatable writing style makes learning intuitive. Who is it for? The ideal readers of this book are data professionals aiming to achieve CompTIA Data+ certification (DAO-001 exam), individuals entering the growing field of data analytics, and professionals looking to validate or expand their skills. Whether you're starting from scratch or solidifying your knowledge, this book is designed for all levels.

The chapters in this book deal with Basic formulation of waveguide cavity resonator equations. The reviews of basic statistical signal processing. The Hartree-Fock equations.

Manage and Automate Data Analysis with Pandas in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple data sets. Pandas for Everyone, 2nd Edition, brings together practical knowledge and insight for solving real problems with Pandas, even if youre new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world data science problems such as using regularization to prevent data overfitting, or when to use unsupervised machine learning methods to find the underlying structure in a data set. New features to the second edition include: Extended coverage of plotting and the seaborn data visualization library Expanded examples and resources Updated Python 3.9 code and packages coverage, including statsmodels and scikit-learn libraries Online bonus material on geopandas, Dask, and creating interactive graphics with Altair Chen gives you a jumpstart on using Pandas with a realistic data set and covers combining data sets, handling missing data, and structuring data sets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes. Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability and introduces you to the wider Python data analysis ecosystem. Work with DataFrames and Series, and import or export data Create plots with matplotlib, seaborn, and pandas Combine data sets and handle missing data Reshape, tidy, and clean data sets so theyre easier to work with Convert data types and manipulate text strings Apply functions to scale data manipulations Aggregate, transform, and filter large data sets with groupby Leverage Pandas advanced date and time capabilities Fit linear models using statsmodels and scikit-learn libraries Use generalized linear modeling to fit models with different response variables Compare multiple models to select the best one Regularize to overcome overfitting and improve performance Use clustering in unsupervised machine learning ...

Prepare smarter, faster, and better with the premier study guide for Snowflake SnowPro Core certification Snowflake, a cloud-based data warehousing platform, has steadily gained popularity since its 2014 launch. Snowflake offers several certification exams, of which the SnowPro Core certification is the foundational exam. The SnowPro Core Certification validates an individual's grasp of Snowflake as a cloud data warehouse, its architectural fundamentals, and the ability to design, implement, and maintain secure, scalable Snowflake systems. The Snowflake SnowPro Core Certification Study Guide delivers comprehensive coverage of every relevant exam topic on the Snowflake SnowPro Core Certification test. Prepare efficiently and effectively for the exam with online practice tests and flashcards, a digital glossary, and concise and easy-to-follow instruction from the subject-matter experts at Sybex. You'll gain the necessary knowledge to help you succeed in the exam and will be able to apply the acquired practical skills to real-world Snowflake solutions. This Study Guide includes: Comprehensive understanding of Snowflake's unique shared data, multi-cluster architecture Guidance on loading structured and semi-structured data into Snowflake Utilizing data sharing, cloning, and time travel features Managing performance through clustering keys, scaling compute up, down & across Steps to account management and security configuration including RBAC & MFA All the info you need to obtain a highly valued credential for a rapidly growing new database software solution Access to the Sybex online learning center, with chapter review questions, full-length practice exams, hundreds of electronic flashcards, and a glossary of key terms Perfect for anyone considering a new career in cloud-based data warehouse solutions and related fields, Snowflake SnowPro Core Certification Study Guide is also a must-read for veteran database professionals seeking an understanding of one of the newest and fastest-growing niches in data.

"An Ethical Guide to Cyber Anonymity" is a comprehensive resource for understanding and safeguarding your privacy while navigating the internet. By the end of this book, you will have gained the skills and knowledge to maintain your cyber anonymity, ensuring your activities online remain private and secure. What this Book will help me do Understand the fundamental concepts of cyber anonymity and internet privacy. Learn practical methods to protect your identity from being compromised online. Gain expertise in configuring tools to achieve a secure and anonymous online presence. Identify and mitigate risks associated with privacy threats from various entities. Master techniques to ensure safe and private internet usage for yourself and others. Author(s) Kushantha Gunawardana is a seasoned expert in cybersecurity with years of experience in dealing with cyber anonymity and data protection. With a passion for educating others, Kushantha translates complex technical ideas into accessible and actionable knowledge. Their approach combines in-depth technical expertise with a focus on ethical practices and real-world applications. Who is it for? This book is ideal for journalists, ethical hackers, and cybersecurity professionals who are striving to protect their anonymity online. It is also a great resource for security-aware individuals looking to safeguard their personal privacy. Beginners or intermediates in the field of web privacy who aim to strengthen their understanding will find this book highly valuable. Parents wishing to protect their family's online identity can also benefit from its guidance.

Cybersecurity and privacy compliance are critical to protecting organizations from data breaches and fines. In the "Cybersecurity and Privacy Law Handbook," you'll find practical, beginner-friendly guidance to understand standards, identify gaps, and implement policies to secure your workplace effectively. What this Book will help me do Understand international cybersecurity standards such as ISO27001 and NIST. Identify and analyze security gaps using gap analysis and business impact methodologies. Ensure compliance with privacy laws like GDPR, HIPAA, and FTC regulations. Develop and implement effective cybersecurity policies and procedures. Navigate complex US-specific privacy regulations and their implications. Author(s) None Rocchi is an experienced author and practitioner in cybersecurity and privacy. With extensive knowledge in international compliance standards, they excel in breaking down complex topics into digestible and actionable content. Their practical and approachable writing style makes tackling the technical and legal facets of cybersecurity straightforward and engaging. Who is it for? This book is tailored for professionals new to cybersecurity and privacy who wish to understand and implement fundamental practices in this domain. It is ideal for managers, students, or experts from other fields looking to manage security functions effectively. No prior deep technical knowledge is required, making it friendly for beginners.

This comprehensive guide, "Graph Data Processing with Cypher," provides a clear and practical approach to mastering Cypher for querying Neo4j graph databases. Packed with real-world examples and detailed explanations, you'll learn how to model graph data, write and optimize Cypher queries, and leverage advanced features to extract meaningful insights from your data. What this Book will help me do Master the Cypher query language, from basics to advanced graph traversal techniques. Develop graph data models based on real-world business requirements and efficiently load data. Optimize Cypher queries for performance through query profiling and tuning techniques. Enhance Cypher's capabilities using APOC utilities for advanced data processing. Create impactful visualizations of graph data using tools like Neo4j Bloom. Author(s) Ravindranatha Anthapu has vast expertise in graph databases and years of professional experience working with Cypher and Neo4j. He brings a hands-on and accessible approach to teaching technical concepts, aiming to empower developers to effectively use graph databases. Through a passion for knowledge-sharing, Ravindranatha ensures readers feel both supported and challenged in their learning journey. Who is it for? This book is ideal for database administrators, developers, and architects, especially those who work with graph databases or want to transition into this domain. Beginners with basic Cypher knowledge and professionals aiming to advance their graph modeling and query optimization skills will find this resource invaluable. It is especially beneficial for individuals seeking to harness the full potential of Neo4j graph databases through Cypher.

Updated throughout for the third edition, Kinematics and Dynamics of Mechanical Systems: Implementation in MATLAB® and Simscape Multibody™ offers step-by-step instruction on the fundamentals of mechanism kinematics, synthesis, statics and dynamics, alongside demonstrating its real-world applications.

Explore the capabilities of Oracle Autonomous Database (ADB) to improve enterprise-level data management. Through this book, you will dive deep into deploying, managing, and securing ADBs using Oracle Cloud Infrastructure (OCI). Gain hands-on experience with high-availability setups, data migration methods, and advanced security measures to elevate your enterprise architecture. What this Book will help me do Understand the key considerations for planning, migrating, and maintaining Oracle Autonomous Databases. Learn to implement high availability solutions using Autonomous Data Guard in ADB environments. Master the configuration of backup, restore, and disaster recovery strategies within OCI. Implement advanced security practices including encryption and IAM policy management. Gain proficiency in leveraging ADB features like APEX, SQL Developer Web, and REST APIs for rapid application development. Author(s) The authors None Sharma, Krishnakumar KM, and None Panda are experts in database systems, particularly in Oracle technologies. With years of hands-on experience implementing enterprise solutions and training professionals, they have pooled their knowledge to craft a resource-rich guide filled with practical advice. Who is it for? This book is ideal for cloud architects, database administrators, and implementation consultants seeking to leverage Oracle's Autonomous Database for enhanced automation, security, and scalability. It is well-suited for professionals with foundational knowledge of Linux, OCI, and databases. Aspiring cloud engineers and students aiming to understand modern database management will also benefit greatly.

How do you turn raw, unprocessed, or malformed data into dynamic, interactive web visualizations? In this practical book, author Kyran Dale shows data scientists and analysts--as well as Python and JavaScript developers--how to create the ideal toolchain for the job. By providing engaging examples and stressing hard-earned best practices, this guide teaches you how to leverage the power of best-of-breed Python and JavaScript libraries. Python provides accessible, powerful, and mature libraries for scraping, cleaning, and processing data. And while JavaScript is the best language when it comes to programming web visualizations, its data processing abilities can't compare with Python's. Together, these two languages are a perfect complement for creating a modern web-visualization toolchain. This book gets you started. You'll learn how to: Obtain data you need programmatically, using scraping tools or web APIs: Requests, Scrapy, Beautiful Soup Clean and process data using Python's heavyweight data processing libraries within the NumPy ecosystem: Jupyter notebooks with pandas+Matplotlib+Seaborn Deliver the data to a browser with static files or by using Flask, the lightweight Python server, and a RESTful API Pick up enough web development skills (HTML, CSS, JS) to get your visualized data on the web Use the data you've mined and refined to create web charts and visualizations with Plotly, D3, Leaflet, and other libraries

This IBM® Redbooks® publication provides both introductory information and technical details for ISV IBM Z® Program Development Tool (IBM zPDT®), which produces a small IBM zSystems environment that is suitable for application development. ISV zPDT is a personal computer (PC) Linux application. When ISV zPDT is installed on Linux, normal IBM zSystems operating systems (such as IBM z/OS®) may be run on it. ISV zPDT provides the basic IBM zSystems architecture and provides emulated IBM 3390 disk drives, 3270 interfaces, Open Systems Adapter (OSA) interfaces, and other items. The systems that are described in this publication are complex, with elements of Linux (for the underlying PC machine), IBM z/Architecture® (for the core zPDT elements), IBM zSystems I/O functions (for emulated I/O devices), z/OS (the most common IBM zSystems operating system), and various applications and subsystems under z/OS. We assume that the reader is familiar with general concepts and terminology of IBM zSystems hardware and software elements, and with basic PC Linux characteristics. This publication provides the primary documentation for ISV zPDT and corresponds to zPDT V1 R11, commonly known as GA11.

The focus of this document is to highlight early threat detection by using Splunk Enterprise and proactively start a cyber resilience workflow in response to a cyberattack or malicious user action. The workflow uses IBM® Copy Services Manager (CSM) as orchestration software to invoke the IBM FlashSystem® storage Safeguarded Copy function, which creates an immutable copy of the data in an air-gapped form on the same IBM FlashSystem Storage for isolation and eventual quick recovery. This document explains the steps that are required to enable and forward IBM FlashSystem audit logs and set a Splunk forwarder configuration to forward local event logs to Splunk Enterprise. This document also describes how to create various alerts in Splunk Enterprise to determine a threat, and configure and invoke an appropriate response to the detected threat in Splunk Enterprise. This document explains the lab setup configuration steps that are involved in configuring various components like Splunk Enterprise, Splunk Enterprise config files for custom apps, IBM CSM, and IBM FlashSystem Storage. The last steps in the lab setup section demonstrate the automated Safeguarded Copy creation and validation steps. This document also describes brief steps for configuring various components and integrating them. This document demonstrates a use case for protecting a Microsoft SQL database (DB) volume that is created on IBM FlashSystem Storage. When a threat is detected on the Microsoft SQL DB volume, Safeguarded Copy starts on an IBM FlashSystem Storage volume. The Safeguarded Copy creates an immutable copy of the data, and the same data volume can be recovered or restored by using IBM CSM. This publication does not describe the installation procedures for Splunk Enterprise, Splunk Forwarder for IBM CSM, th Microsoft SQL server, or the IBM FlashSystem Storage setup. It is assumed that the reader of the book has a basic understanding of system, Windows, and DB administration; storage administration; and has access to the required software and documentation that is used in this document.

More organizations than ever understand the importance of data lake architectures for deriving value from their data. Building a robust, scalable, and performant data lake remains a complex proposition, however, with a buffet of tools and options that need to work together to provide a seamless end-to-end pipeline from data to insights. This book provides a concise yet comprehensive overview on the setup, management, and governance of a cloud data lake. Author Rukmani Gopalan, a product management leader and data enthusiast, guides data architects and engineers through the major aspects of working with a cloud data lake, from design considerations and best practices to data format optimizations, performance optimization, cost management, and governance. Learn the benefits of a cloud-based big data strategy for your organization Get guidance and best practices for designing performant and scalable data lakes Examine architecture and design choices, and data governance principles and strategies Build a data strategy that scales as your organizational and business needs increase Implement a scalable data lake in the cloud Use cloud-based advanced analytics to gain more value from your data

The focus of this IBM® blueprint is to showcase the Read Diagnostic Parameters (RDP) feature of the Fibre Channel protocol (FCP). The data that is provided by RDP commands can simplify the process of managing and analyzing any issues on complex SAN fabrics. In this blueprint, we provide guidance to help users and administrators understand the meaning of RDP data and how to use it. The intent of this blueprint is to help a user understand what RDP is, what data RDP represents, and how to use that data to identify potential issues within the SAN fabric that is hosted by that Fibre Channel (FC) switch.

Learn how to integrate data-driven methodologies and machine learning into your business decision-making processes with 'The Art of Data-Driven Business.' This comprehensive guide shows you how to apply Python-based machine learning techniques to real-world challenges, transforming your organization into an innovative and well-informed enterprise. What this Book will help me do Create professional-quality data visualizations using Python's seaborn library to derive business insights. Analyze customer behavior, including predicting churn, with machine learning techniques. Apply clustering algorithms to segment customers for targeted marketing campaigns. Utilize pandas effectively for pricing and sales analytics to optimize your pricing strategies. Forecast outcomes of promotional strategies to determine costs and benefits and maximize performance. Author(s) None Palacio is an experienced data scientist and educator who specializes in the application of machine learning to solve business problems. With extensive real-world industry experience, Palacio brings practical insights and methodologies to learners. Their teaching connects technical knowledge to actionable business strategies. Who is it for? This book is ideal for business professionals aiming to incorporate data science into their strategies and technical experts seeking to leverage machine learning for business scenarios. Beginners to Python can find foundational help, while data scientists will appreciate the focused practical applications. It's perfect for individuals seeking a strong data-driven perspective in marketing, sales, and customer management.

FUZZY COMPUTING IN DATA SCIENCE This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges. The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation. Audience Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.

"Data Literacy in Practice" teaches readers to unlock the power of data for making smarter decisions. You'll learn how to understand and work with data, gain the ability to derive actionable insights, and develop the skills required for data-informed decision-making. What this Book will help me do Understand the basics of data literacy and the importance of data in decision-making. Learn to visualize data effectively using charts and graphs tailored to your audience. Master the application of the four-pillar model for organizational data literacy advancement. Develop proficiency in managing data environments and assessing data quality. Become competent in deriving actionable insights and critical questioning for better analysis. Author(s) Angelika Klidas and Kevin Hanegan are pioneers in the field of data literacy with extensive experience in data analytics. Both are seasoned educators at top universities and bring their expertise to this book to help readers understand and leverage the power of data. Who is it for? "Data Literacy in Practice" is ideal for data analysts, professionals, and teams looking to enhance their data literacy skills. Readers should have a desire to utilize data effectively in their roles, regardless of prior experience. The book is designed to guide both beginners starting out and those who aim to deepen their knowledge.

In today's fast-paced, ever-growing digital world, you face various new and complex business problems. To help resolve these problems, enterprises are embedding artificial intelligence (AI) into their mission-critical business processes and applications to help improve operations, optimize performance, personalize the user experience, and differentiate themselves from the competition. Furthermore, the use of AI on the IBM® zSystems platform, where your mission-critical transactions, data, and applications are installed, is a key aspect of modernizing business-critical applications while maintaining strict service-level agreements (SLAs) and security requirements. This colocation of data and AI empowers your enterprise to optimally and easily deploy and infuse AI capabilities into your enterprise workloads with the most recent and relevant data available in real time, which enables a more transparent, accurate, and dependable AI experience. This IBM Redpaper publication introduces and explains AI technologies and hardware optimizations, such as IBM zSystems Integrated Accelerator for AI, and demonstrates how to leverage certain capabilities and components to enable solutions in business-critical use cases, such as fraud detection and credit risk scoring on the platform. Real-time inferencing with AI models, a capability that is critical to certain industries and use cases such as fraud detection, now can be implemented with optimized performance thanks to innovations like IBM zSystems Integrated Accelerator for AI embedded in the Telum chip within IBM z16™. This publication also describes and demonstrates the implementation and integration of the two end-to-end solutions (fraud detection and credit risk), from developing and training the AI models to deploying the models in an IBM z/OS® V2R5 environment on IBM z16 hardware, and to integrating AI functions into an application, for example an IBM z/OS Customer Information Control System (IBM CICS®) application. We describe performance optimization recommendations and considerations when leveraging AI technology on the IBM zSystems platform, including optimizations for micro-batching in IBM Watson® Machine Learning for z/OS (WMLz). The benefits that are derived from the solutions also are described in detail, which includes how the open-source AI framework portability of the IBM zSystems platform enables model development and training to be done anywhere, including on IBM zSystems, and the ability to easily integrate to deploy on IBM zSystems for optimal inferencing. You can uncover insights at the transaction level while taking advantage of the speed, depth, and securability of the platform. This publication is intended for technical specialists, site reliability engineers, architects, system programmers, and systems engineers. Technologies that are covered include TensorFlow Serving, WMLz, IBM Cloud Pak® for Data (CP4D), IBM z/OS Container Extensions (zCX), IBM Customer Information Control System (IBM CICS), Open Neural Network Exchange (ONNX), and IBM Deep Learning Compiler (zDLC).

Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, experienced software architecture practitioners Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while reducing single points of failure and manual scheduling. Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. If your data processing or server application has grown beyond what a single computer can handle, this book is for you. You'll explore distributed processing (the pure Python implementation of serverless) and learn how to: Implement stateful applications with Ray actors Build workflow management in Ray Use Ray as a unified system for batch and stream processing Apply advanced data processing with Ray Build microservices with Ray Implement reliable Ray applications

Get your daily work done efficiently using this comprehensive guide for SQL Server DBAs that covers all that a practicing database administrator needs to know. Updated for SQL Server 2022, this edition includes coverage of new features, such as Ledger, which provides an immutable record of table history to protect you against malicious data tampering, and integration with cloud providers to support hybrid cloud scenarios. You’ll also find new content on performance optimizations, such as query pan feedback, and security controls, such as new database roles, which are restructured for modern ways of working. Coverage also includes Query Store, installation on Linux, and the use of containerized SQL. Pro SQL Server 2022 Administration takes DBAs on a journey that begins with planning their SQL Server deployment and runs through installing and configuring the instance, administering and optimizing database objects, and ensuring that data issecure and highly available. Readers will learn how to perform advanced maintenance and tuning techniques, and discover SQL Server's hybrid cloud functionality. This book teaches you how to make the most of new SQL Server 2022 functionality, including integration for hybrid cloud scenarios. The book promotes best-practice installation, shows how to configure for scalability and high availability, and demonstrates the gamut of database-level maintenance tasks, such as index maintenance, database consistency checks, and table optimizations. What You Will Learn Integrate SQL Server with Azure for hybrid cloud scenarios Audit changes and prevent malicious data changes with SQL Server’s Ledger Secure and encrypt data to protect against embarrassing data breaches Ensure 24 x 7 x 365 access through high availability and disaster recovery features in today’s hybrid world Use Azure tooling, including Arc, to gain insight into and manage your SQL Server enterprise Install and configure SQL Server on Windows, Linux, and in containers Perform routine maintenance tasks, such as backups and database consistency checks Optimize performance and undertake troubleshooting in the Database Engine Who This Book Is For SQL Server DBAs who manage on-premise installations of SQL Server. This book is also useful for DBAs who wish to learn advanced features, such as integration with Azure, Query Store, Extended Events, and Policy-Based Management, or those who need to install SQL Server in a variety of environments.