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Geared to intermediate- to advanced-level DBAs and IT professionals looking to enhance their MySQL skills, this guide provides a comprehensive overview on how to manage and optimize MySQL databases. You'll learn how to create databases and implement backup and recovery, security configurations, high availability, scaling techniques, and performance tuning. Using practical techniques, tips, and real-world examples, authors Arunjith Aravindan and Jeyaram Ayyalusamy show you how to deploy and manage MySQL, Amazon RDS, Amazon Aurora, and Azure MySQL. By the end of the book, you'll have the knowledge and skills necessary to administer, manage, and optimize MySQL databases effectively. Design and implement a scalable and reliable database infrastructure using MySQL 8 on premises and cloud Install and configure software, manage user accounts, and optimize database performance Use backup and recovery strategies, security measures, and high availability solutions Apply best practices for database schema design, indexing strategies, and replication techniques Implement advanced database features and techniques such as replication, clustering, load balancing, and high availability Troubleshoot common issues and errors, using diagnostic tools and techniques to identify and resolve problems quickly and efficiently Facilitate major MySQL upgrades including MySQL 5.7 to MySQL 8

Jack the Ripper and legacy codebases have more in common than you'd think. Inspired by forensic psychology methods, you can apply strategies to identify problems in your existing code, assess refactoring direction, and understand how your team influences the software architecture. With its unique blend of criminal psychology and code analysis, Your Code as a Crime Scene arms you with the techniques you need to take on any codebase, no matter what programming language you use. Software development might well be the most challenging task humanity ever attempted. As systems scale up, they also become increasingly complex, expensive to maintain, and difficult to reason about. We can always write more tests, try to refactor, and even fire up a debugger to understand complex coding constructs. That's a great starting point, but you can do so much better. Take inspiration from forensic psychology techniques to understand and improve existing code. Visualize codebases via a geographic profile from commit data to find development hotspots, prioritize technical debt, and uncover hidden dependencies. Get data and develop strategies to make the business case for larger refactorings. Detect and fix organizational problems from the vantage point of the software architecture to remove bottlenecks for the teams. The original Your Code as a Crime Scene from 2014 pioneered techniques for understanding the intersection of people and code. This new edition reflects a decade of additional experience from hundreds of projects. Updated techniques, novel case studies, and extensive new material adds to the strengths of this cult classic. Change how you view software development and join the hunt for better code! What You Need: You need to be comfortable reading code. You also need to use Git (or Subversion, Mercurial or similar version-control tool).

Augmented Analytics isn't just another book on data and analytics; it's a holistic resource for reimagining how your entire organization interacts with information so that it becomes insight-driven. Go beyond traditional, limited ways of making sense of data. Augmented Analytics provides a dynamic, actionable strategy for improving your organization's analytical capabilities. With this book, you can infuse your workflows with intelligent automation and modern artificial intelligence, empowering more team members to make informed, data-driven decisions. Be aware: This book is not just about adding another forecast to your dashboard. It goes deeper, presenting a holistic approach to fostering a data-driven culture of analytics excellence throughout your organization. You'll explore: Key elements and building blocks of augmented analytics, including its benefits, potential challenges, and relevance in today's business landscape Best practices for preparing and implementing augmented analytics in your organization, including analytics roles, mindset, toolset, and skill set Best practices for data enablement, liberalization, trust, and accessibility How to apply a use case approach to drive business value and use augmented analytics as an enabler, with selected case studies Drawing on extensive, real-world experience leading large organizations through this transformation, the authors provide a clear, actionable path to accelerate your organization's journey to analytical excellence.

A decade ago, developers built information-sharing software by writing a lot of custom code in a single code base, then adding layers of caching. Now we build information systems: interdependent software and services, data platforms, and event streams. Many of our software-to-systems initiatives fail, though, and when they do, we double down on traditional linear approaches. But linear thinking cannot resolve systems challenges. We need to shift to systems thinking. This book shows software developers and architects how systems thinking can guide you through the emerging complexity of modern systems. Author Diana Montalion presents a vision of technology architecture that transforms how we learn, communicate, and collaborate with others. Through practical examples and scenarios, you'll learn how to develop critical self-reflection and decision-making skills amid complexity and uncertainty--and lead impactful cultural change within your organization. You'll learn: How linear thinking limits your perspective on software systems The obstacles to changing your perspective and how to move past them How systems and nonlinear thinking help you understand and navigate complex issues arising from internal and external factors Methods for creating sound, cross-functional recommendations in the midst of complexity and uncertainty How nonlinear approaches improve the quality of architectural thinking and deliver impactful change for organizations How to provide a modern style of leadership as software becomes information systems

JavaScript gives web developers great power to create rich interactive browser experiences, and much of that power is provided by the browser itself. Modern web APIs enable web-based applications to come to life like never before, supporting actions that once required browser plug-ins. Some are still in an experimental stage, but many are ready for use today. With this hands-on cookbook, author Joe Attardi helps you explore the powerful APIs available in modern browsers and guides you through the specific tasks that they unlock. Because these features are web standards, there is comprehensive documentation available from trusted resources such as MDN Web Docs. The knowledge you'll gain is transferable across different companies and projects. Learn the breadth of functionality available in modern browser APIs Explore future APIs that are still in an experimental stage Discover newer elements, such as dialog that replaces the need for a third-party library Build more powerful and interactive web applications using native APIs Understand the permissions model used by the browser to unlock functionality such as geolocation and push notifications

In today's fast-paced world, more and more organizations require rapid application development with reduced development costs and increased productivity. This practical guide shows application developers how to use PowerApps, Microsoft's no-code/low-code application framework that helps developers speed up development, modernize business processes, and solve tough challenges. Author Arpit Shrivastava provides a comprehensive overview of designing and building cost-effective applications with Microsoft Power Apps. You'll learn fundamental concepts behind low-code and no-code development, how to build applications using pre-built and blank templates, how to design an app using Copilot AI and drag and drop PowerPoint-like controls, use Excel-like expressions to write business logic for an app, and integrate apps with external data sources. With this book, you'll: Learn the importance of no-code/low-code application development Design mobile/tablet (canvas apps) applications using pre-built and blank templates Design web applications (model-driven apps) using low-code, no-code, and pro-code components Integrate PowerApps with external applications Learn basic coding concepts like JavaScript, Power Fx, and C# Apply best practices to customize Dynamics 365 CE applications Dive into Azure DevOps and ALM concepts to automate application deployment Citizen developers and professional application developers alike will be able to design robust applications and solve real world business challenges using Power Apps. Arpit Shrivastava is a Microsoft MVP and Power Platform architect at Capgemini, with vast experience working with Microsoft Dynamics 365 and the Power Platform.

Methods of delivering software are constantly evolving in order to increase speed to market without sacrificing reliability and stability. Mastering development end to end, from version control to production, and building production-ready code is now more important than ever. Continuous deployment takes it one step further. This method for delivering software automates the final step to production and enables faster feedback and safer releases. Based on years of work with medium to large organizations at Thoughtworks, author Valentina Servile explains how to perform safe and reliable deployments with no manual gate to production. You'll learn a framework to perform incremental, safe releases during everyday development work, structured exclusively around the challenges of continuous deployment in nontrivial, distributed systems. Complete with interviews and case studies from fellow industry professionals. Close the feedback loop and leverage the production environment to manage your end-to-end development lifecycle efficiently. This book helps you: Take observability, performance, test automation, and security into account when splitting work into increments Create a daily development plan that takes immediate deployments to production into account Deploy work in progress to production incrementally without causing regressions Use patterns to refactor live functionality and alter persistence layers Test and release features in production using different feature toggle configurations

Data science happens in code. The ability to write reproducible, robust, scaleable code is key to a data science project's success--and is absolutely essential for those working with production code. This practical book bridges the gap between data science and software engineering, clearly explaining how to apply the best practices from software engineering to data science. Examples are provided in Python, drawn from popular packages such as NumPy and pandas. If you want to write better data science code, this guide covers the essential topics you need (and that are often missing from introductory data science or coding classes), including how to: Understand data structures and object-oriented programming Clearly and skillfully document your code Package and share your code Integrate data science code with a larger codebase Write APIs Create secure code Apply best practices to common tasks such as testing, error handling, and logging Work more effectively with software engineers Write more efficient, maintainable, and robust code in Python Put your data science projects into production And more

"Python is an excellent way to get started in programming, and this clear, concise guide walks you through Python a step at a time--beginning with basic programming concepts before moving on to functions, data structures, and object-oriented design."--

Keeping up with the Python ecosystem can be daunting. Its developer tooling doesn't provide the out-of-the-box experience native to languages like Rust and Go. When it comes to long-term project maintenance or collaborating with others, every Python project faces the same problem: how to build reliable workflows beyond local development while staying in sync with the evolving ecosystem. With this hands-on guide, Python developers will learn how to forge the moving parts of a Python project into an easy-to-use toolchain, using state-of-the-art tools including Poetry, Nox, pytest, mypy, pre-commit, Black, Ruff, uv, Rye, Hatch, and more. Author Claudio Jolowicz shows you how to create robust Python project structures complete with unit tests, static analysis, code formatting, and type checking. You'll learn how to: Create open source projects with state-of-the-art infrastructure Build a custom infrastructure for all Python projects in a company or team Improve and modernize the infrastructure of an existing Python project Evaluate modern Python tooling for adoption in existing projects Use tools for packaging and dependency management Automate common development tasks such as testing, dependency updates, and publishing releases

How will software development and operations have to change to meet the sustainability and green needs of the planet? And what does that imply for development organizations? In this eye-opening book, sustainable software advocates Anne Currie, Sarah Hsu, and Sara Bergman provide a unique overview of this topic-discussing everything from the likely evolution of national grids to the effect those changes will have on the day-to-day lives of developers. Ideal for everyone from new developers to CTOs, Building Green Software tackles the challenges involved and shows you how to build, host, and operate code in a way that's not only better for the planet, but also cheaper and relatively low-risk for your business. Most hyperscale public cloud providers have already committed to net-zero IT operations by 2030. This book shows you how to get on board.

p>If you thought data structures and algorithms were all just theory, you're missing out on what they can do for your Python code. Learn to use Big O notation to make your code run faster by orders of magnitude. Choose from data structures such as hash tables, trees, and graphs to increase your code's efficiency exponentially. With simple language and clear diagrams, this book makes this complex topic accessible, no matter your background. Every chapter features practice exercises to give you the hands-on information you need to master data structures and algorithms for your day-to-day work. Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. Take a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. The Python edition uses Python exclusively for all code examples, exercise, and solutions. Use Big O notation to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Practice your new skills with exercises in every chapter, along with detailed solutions. Use these techniques today to make your Python code faster and more scalable.

In today's cloud native world, where we automate as much as possible, everything is code. With this practical guide, you'll learn how Policy as Code (PaC) provides the means to manage the policies, related data, and responses to events that occur within the systems we maintain--Kubernetes, cloud security, software supply chain security, infrastructure as code, and microservices authorization, among others. Author Jimmy Ray provides a practical approach to integrating PaC solutions into your systems, with plenty of real-world examples and important hands-on guidance. DevOps and DevSecOps engineers, Kubernetes developers, and cloud engineers will understand how to choose and then implement the most appropriate solutions. Understand PaC theory, best practices, and use cases for security Learn how to choose and use the correct PaC solution for your needs Explore PaC tooling and deployment options for writing and managing PaC policies Apply PaC to DevOps, IaC, Kubernetes, and AuthN/AuthZ Examine how you can use PaC to implement security controls Verify that your PaC solution is providing the desired result Create auditable artifacts to satisfy internal and external regulatory requirements

"C# is undeniably one of the most versatile programming languages available to engineers today. With this comprehensive guide, you'll learn just how powerful the combination of C# and .NET can be. Author Ian Griffiths guides you through C# 12.0 and .NET 8 fundamentals and techniques for building cloud, web, and desktop applications. Designed for experienced programmers, this book provides many code examples to help you work with the nuts and bolts of C#, such as generics, LINQ, and asynchronous programming features. You'll get up to speed on .NET 8 and the latest C# 11.0 and 12.0 additions, including generic math, new polymorphism options, enhanced pattern matching, and new features designed to improve productivity. This book helps you: Understand how .NET has changed in recent releases and learn what it means for application development; Select the appropriate C# language features for any task; Learn when to use the new features and when to stick with older ones; Examine the range of functionality in .NET's class libraries; Apply these class libraries to practical programming tasks; Explore numerous small additions to .NET that improve expressiveness"--

In today's data-driven world, understanding statistical models is crucial for effective analysis and decision making. Whether you're a beginner or an experienced user, this book equips you with the foundational knowledge to grasp and implement statistical models within Tableau. Gain the confidence to speak fluently about the models you employ, driving adoption of your insights and analysis across your organization. As AI continues to revolutionize industries, possessing the skills to leverage statistical models is no longer optional--it's a necessity. Stay ahead of the curve and harness the full potential of your data by mastering the ability to interpret and utilize the insights generated by these models. Whether you're a data enthusiast, analyst, or business professional, this book empowers you to navigate the ever-evolving landscape of data analytics with confidence and proficiency. Start your journey toward data mastery today. In this book, you will learn: The basics of foundational statistical modeling with Tableau How to prove your analysis is statistically significant How to calculate and interpret confidence intervals Best practices for incorporating statistics into data visualizations How to connect external analytics resources from Tableau using R and Python

"How do some organizations maintain 24-7 internet-scale operations? How can organizations integrate security while continuously deploying new features? How do organizations increase security within their DevOps processes? This practical guide helps you answer those questions and more. Author Steve Suehring provides unique content to help practitioners and leadership successfully implement DevOps and DevSecOps. Learning DevSecOps emphasizes prerequisites that lead to success through best practices and then takes you through some of the tools and software used by successful DevSecOps-enabled organizations. You'll learn how DevOps and DevSecOps can eliminate the walls that stand between development, operations, and security so that you can tackle the needs of other teams early in the development lifecycle. This book helps you: Learn why DevSecOps is about culture and processes, with tools to support the processes; Understand why DevSecOps practices are key elements to deploying software in a 24-7 environment; Deploy software using a DevSecOps toolchain and create scripts to assist; Integrate processes from other teams earlier in the software development lifecycle; Help team members learn the processes important for successful software development"--

Rust's popularity is growing, due in part to features like memory safety, type safety, and thread safety. But these same elements can also make learning Rust a challenge, even for experienced programmers. This practical guide helps you make the transition to writing idiomatic Rust--while also making full use of Rust's type system, safety guarantees, and burgeoning ecosystem. If you're a software engineer who has experience with an existing compiled language, or if you've struggled to convert a basic understanding of Rust syntax into working programs, this book is for you. By focusing on the conceptual differences between Rust and other compiled languages, and by providing specific recommendations that programmers can easily follow, Effective Rust will soon have you writing fluent Rust, not just badly translated C++. Understand the structure of Rust's type system Learn Rust idioms for error handling, iteration, and more Discover how to work with Rust's crate ecosystem Use Rust's type system to express your design Win fights with the borrow checker Build a robust project that takes full advantage of the Rust tooling ecosystem

The walls were closing in on Bruce and Maggie Tate. Isolation forced on them by the pandemic, combined with America's growing political factionalism, threatened their bonds with community and family. Something had to change. Maggie's surprising answer: buy a boat, learn to pilot it, and embark on the Great Loop. For nine months Bruce and Maggi

Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required. This book illustrates complex concepts of full stack deep learning and reinforces them through hands-on exercises to arm you with tools and techniques to scale your project. A scaling effort is only beneficial when it's effective and efficient. To that end, this guide explains the intricate concepts and techniques that will help you scale effectively and efficiently. You'll gain a thorough understanding of: How data flows through the deep-learning network and the role the computation graphs play in building your model How accelerated computing speeds up your training and how best you can utilize the resources at your disposal How to train your model using distributed training paradigms, i.e., data, model, and pipeline parallelism How to leverage PyTorch ecosystems in conjunction with NVIDIA libraries and Triton to scale your model training Debugging, monitoring, and investigating the undesirable bottlenecks that slow down your model training How to expedite the training lifecycle and streamline your feedback loop to iterate model development A set of data tricks and techniques and how to apply them to scale your training model How to select the right tools and techniques for your deep-learning project Options for managing the compute infrastructure when running at scale

Data modeling is the single most overlooked feature in Power BI Desktop, yet it's what sets Power BI apart from other tools on the market. This practical book serves as your fast-forward button for data modeling with Power BI, Analysis Services tabular, and SQL databases. It serves as a starting point for data modeling, as well as a handy refresher. Author Markus Ehrenmueller-Jensen, founder of Savory Data, shows you the basic concepts of Power BI's semantic model with hands-on examples in DAX, Power Query, and T-SQL. If you're looking to build a data warehouse layer, chapters with T-SQL examples will get you started. You'll begin with simple steps and gradually solve more complex problems. This book shows you how to: Normalize and denormalize with DAX, Power Query, and T-SQL Apply best practices for calculations, flags and indicators, time and date, role-playing dimensions and slowly changing dimensions Solve challenges such as binning, budget, localized models, composite models, and key value with DAX, Power Query, and T-SQL Discover and tackle performance issues by applying solutions in DAX, Power Query, and T-SQL Work with tables, relations, set operations, normal forms, dimensional modeling, and ETL

"Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each. James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You'll learn what data lakehouses can help you achieve, and how to distinguish data mesh hype from reality. Best of all, you'll be able to determine the most appropriate data architecture for your needs. With this book, you'll: gain a working understanding of several data architectures; learn the strengths and weakness of each approach; distinguish data architecture theory from the reality; pick the best architecture for your use case; understand the differences between data warehouses and data lakes; learn common data architecture concepts to help you build better solutions; explore the historical evolution and characteristics of data architectures; learn essentials of running an architecture design session, team organization, and project success factors."--

If you use Linux in your day-to-day work, then Linux Pocket Guide is the perfect on-the-job reference. This thoroughly updated 20th anniversary edition explains more than 200 Linux commands, including new commands for file handling, package management, version control, file format conversions, and more. In this concise guide, author Daniel Barrett provides the most useful Linux commands grouped by functionality. Whether you're a novice or an experienced user, this practical book is an ideal reference for the most important Linux commands. You'll learn: Essential concepts--commands, shells, users, and the filesystem File commands-creating, organizing, manipulating, and processing files of all kinds Sysadmin basics-superusers, processes, user management, and software installation Filesystem maintenance-disks, RAID, logical volumes, backups, and more Networking commands-working with hosts, network connections, email, and the web Getting stuff done-everything from math to version control to graphics and audio

While many resources for network and IT security are available, detailed knowledge regarding modern web application security has been lackinguntil now. This practical guide provides both offensive and defensive security concepts that software engineers can easily learn and apply.Andrew Hoffman, a senior security engineer at Salesforce, introduces three pillars of web application security: recon, offense, and defense. Youll learn methods for effectively researching and analyzing modern web applicationsincluding those you dont have direct access to. Youll also learn how to break into web applications using the latest hacking techniques. Finally, youll learn how to develop mitigations for use in your own web applications to protect against hackers.Explore common vulnerabilities plaguing today's web applicationsLearn essential hacking techniques attackers use to exploit applicationsMap and document web applications for which you dont have direct accessDevelop and deploy customized exploits that can bypass common defensesDevelop and deploy mitigations to protect your applications against hackersIntegrate secure coding best practices into your development lifecycleGet practical tips to help you improve the overall security of your web applications

"Entity resolution is a key analytic technique that enables you to identify multiple data records that refer to the same real-world entity. With this hands-on guide, product managers, data analysts, and data scientists will learn how to add value to data by cleansing, analyzing, and resolving datasets using open source Python libraries and cloud APIs. Author Michael Shearer shows you how to scale up your data matching processes and improve the accuracy of your reconciliations. You'll be able to remove duplicate entries within a single source and join disparate data sources together when common keys aren't available. Using real-world data examples, this book helps you gain practical understanding to accelerate the delivery of real business value. This book covers: challenges in deduplicating and joining datasets; extracting, cleansing, and preparing datasets for matching; text matching algorithms to identify equivalent entities; techniques for deduplicating and joining datasets at scale; matching datasets containing persons and organizations; optimizing and tuning data matching algorithms; entity resolution using cloud APIs; matching using privacy-enhancing technologies. With entity resolution, you'll build rich and comprehensive data assets that reveal relationships for marketing and risk management purposes, key to harnessing the full potential of machine learning and AI."--

Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service--using powerful generative AI models such as GPT-4 and GPT-4o--within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies

If you haven't modernized your data cleaning and reporting processes in Microsoft Excel, you're missing out on big productivity gains. And if you're looking to conduct rigorous data analysis, more can be done in Excel than you think. This practical book serves as an introduction to the modern Excel suite of features along with other powerful tools for analytics. George Mount of Stringfest Analytics shows business analysts, data analysts, and business intelligence specialists how to make bigger gains right from your spreadsheets by using Excel's latest features. You'll learn how to build repeatable data cleaning workflows with Power Query, and design relational data models straight from your workbook with Power Pivot. You'll also explore other exciting new features for analytics, such as dynamic array functions, AI-powered insights, and Python integration. Learn how to build reports and analyses that were previously difficult or impossible to do in Excel. This book shows you how to: Build repeatable data cleaning processes for Excel with Power Query Create relational data models and analysis measures with Power Pivot Pull data quickly with dynamic arrays Use AI to uncover patterns and trends from inside Excel Integrate Python functionality with Excel for automated analysis and reporting

Great engineers don't necessarily make great leaders -- at least, not without a lot of work. Finding your path to becoming a strong leader is often fraught with challenges. It's not easy to figure out how to be successful, empathetic, and caring yet tough. Whether you're on the management or individual contributor track, you need to develop strong leadership skills. This practical book guides you on the path to becoming a well-rounded and resilient engineering leader."--

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning. Sofien Kaabar--financial author, trading consultant, and institutional market strategist--introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. Understand and create machine learning and deep learning models Explore the details behind reinforcement learning and see how it's used in time series Understand how to interpret performance evaluation metrics Examine technical analysis and learn how it works in financial markets Create technical indicators in Python and combine them with ML models for optimization Evaluate the models' profitability and predictability to understand their limitations and potential

Advance your Power BI skills by adding AI to your repertoire at a practice level. With this practical book, business-oriented software engineers and developers will learn the terminologies, practices, and strategy necessary to successfully incorporate AI into your business intelligence estate.

Filled with tips, tricks, and techniques, this easy-to-use book is the perfect resource for intermediate to advanced users of Excel. You'll find complete recipes for more than a dozen topics covering formulas, PivotTables, charts, Power Query, and more. Each recipe poses a particular problem and outlines a solution that you can put to use right away--without having to comb through tutorial pages. Whether you're a data analyst, project manager, or financial analyst, author Dawn Griffiths directs you straight to the answers you need. Ideal as a quick reference, Excel Cookbook is also perfect for learning how to work in a more efficient way, leading to greater productivity on the job. With this book, you'll jump in and get answers to your questions--fast. This cookbook shows you how to: Get the most out of Excel's features Address complex data problems in the best way possible Collect, manage, and analyze data from a variety of sources Use functions and formulas with ease--including dynamic array and lambda formulas Analyze data with PivotTables, Power Pivot, and more Import and transform data with Power Query Write custom functions and automate Excel with VBA