Kedro is an open-source framework for creating portable pipelines through modular data science code, and provides a powerful interactive visualisation tool called ‘Kedro-Viz’, a webapp that magically generates a highly powerful and informational visualisation of the pipeline.

In 2020, the Kedro project introduced an important set of features to support Modular Pipelines, which allows users to set up a series of pipelines that are logically isolated and re-usable to form higher level pipelines.

With this paradigm shift comes the need to reimagine the visualization of the pipeline on Kedro-viz, in that it needs to introduce a series of redesigns and new features to support this new representation of pipeline structure.

As a core contributor and team member to the Kedro-viz project throughout the past year, I have witnessed the journey of this transition through shipping the core features for modular pipelines on Kedro-viz.

This talk will focus on my experience as a front end developer as I walk through the unique architecture and data ingestion setup for this project. I will deep-dive into the unique set of problems and assumptions we have to make in accommodating this new modular pipeline setup, and our approach for solving them within a Front End(React + Redux) context.

Not to say I will definitely share the mistakes and learnings along the way, and how this paved the path towards the app architecture choices for our next set of features in ML experiment tracking.

This talk is for the curious data practitioner who is up for exposure to a fresh set of problems beyond the typical data science domain, and for those who are up for a ride through the mind-boggling details of the unique set up of front end development and data visualisation for data science.

Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/data... Instagram: https://www.instagram.com/databricksinc/

Dive deep into Microsoft Power BI with the second edition of 'Mastering Microsoft Power BI'. This comprehensive book equips you with the skills to transform business data into actionable insights using Power BI's latest features and techniques. From efficient data retrieval and transformation processes to creating interactive dashboards that tell impactful data stories, you will learn actionable knowledge every step of the way. What this Book will help me do Learn to master data collection and modeling using the Power Query M language Gain expertise in designing DirectQuery, import, and composite data models Understand how to create advanced analytics reports using DAX and Power BI visuals Learn to manage the Power BI environment as an administrator with Premium capacity Develop insightful, scalable, and visually impactful dashboards and reports Author(s) Greg Deckler, a seasoned Power BI expert and solution architect, and None Powell, an experienced BI consultant and data visualization specialist, bring their extensive practical knowledge to this book. Together, they share their real-world expertise and proven techniques applying Power BI's diverse capabilities. Who is it for? This book is ideal for business intelligence professionals and intermediate Power BI users. If you're looking to master data visualization, prepare insightful dashboards, and explore Power BI's full potential, this is for you. Basic understanding of BI concepts and familiarity with Power BI will ensure you get the most value.

R is the most powerful tool you can use for statistical analysis. This definitive guide smooths R’s steep learning curve with practical solutions and real-world applications for commercial environments. In R in Action, Third Edition you will learn how to: Set up and install R and RStudio Clean, manage, and analyze data with R Use the ggplot2 package for graphs and visualizations Solve data management problems using R functions Fit and interpret regression models Test hypotheses and estimate confidence Simplify complex multivariate data with principal components and exploratory factor analysis Make predictions using time series forecasting Create dynamic reports and stunning visualizations Techniques for debugging programs and creating packages R in Action, Third Edition makes learning R quick and easy. That’s why thousands of data scientists have chosen this guide to help them master the powerful language. Far from being a dry academic tome, every example you’ll encounter in this book is relevant to scientific and business developers, and helps you solve common data challenges. R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh coverage of the new tidyverse approach to data analysis and R’s state-of-the-art graphing capabilities with the ggplot2 package. About the Technology Used daily by data scientists, researchers, and quants of all types, R is the gold standard for statistical data analysis. This free and open source language includes packages for everything from advanced data visualization to deep learning. Instantly comfortable for mathematically minded users, R easily handles practical problems without forcing you to think like a software engineer. About the Book R in Action, Third Edition teaches you how to do statistical analysis and data visualization using R and its popular tidyverse packages. In it, you’ll investigate real-world data challenges, including forecasting, data mining, and dynamic report writing. This revised third edition adds new coverage for graphing with ggplot2, along with examples for machine learning topics like clustering, classification, and time series analysis. What's Inside Clean, manage, and analyze data Use the ggplot2 package for graphs and visualizations Techniques for debugging programs and creating packages A complete learning resource for R and tidyverse About the Reader Requires basic math and statistics. No prior experience with R needed. About the Author Dr. Robert I Kabacoff is a professor of quantitative analytics at Wesleyan University and a seasoned data scientist with more than 20 years of experience. Quotes Kabacoff has outdone himself by significantly improving on the already excellent previous edition. - Alain Lompo, ISO-Gruppe R in Action has been my go-to reference on R for years. The third edition contains timely updates on the tidyverse and other new tools. I would recommend this book without hesitation. - Daniel Kenney-Jung MD, Department of Pediatrics, Duke University Outstandingly well-written. The best book on R programming that I have ever read. - Kelvin Meeks, International Technology Ventures Takes the reader through a series of essential methods from basic to complex. The only R book you will ever need. - Martin Perry, Microsoft

Today I talked with João Critis from Oi. Oi is a Brazilian telecommunications company that is a pioneer in convergent broadband services, pay TV, and local and long-distance voice transmission. They operate the largest fiber optics network in Brazil which reaches remote areas to promote digital inclusion of the population. João manages a design team at Oi that is responsible for the front end of data products including dashboards, reports, and all things data visualization. 

We begin by discussing João’s role leading a team of data designers. João then explains what data products actually are, and who makes up his team’s users and customers. João goes on to discuss user adoption challenges at Oi and the methods they use to uncover what users need in the last mile. He then explains the specific challenges his team has faced, particularly with middle management, and how his team builds credibility with senior leadership. In conclusion, João reflects on the value of empathy in the design process. 

In this episode, João shares:  

A data product  (4:48) The research process used by his data teams to build journey maps for clients (7:31) User adoption challenges for Oi (15:27) His answer to the question “how do you decide which mouths to feed?” (16:56) The unique challenges of middle management in delivering useful data products (20:33) The importance of empathy in innovation (25:23) What data scientists need to learn about design and vice versa (27:55)

Quotes from Today’s Episode

“We put the final user in the center of our process. We [conduct] workshops involving co-creation and prototyping, and we test how people work with data.” - João (8:22)

"My first responsibility here is value generation. So, if you have to take two or three steps back, another brainstorm, rethink, and rebuild something that works…. [well], this is very common for us.” - João (19:28)

“If you don’t make an impact on the individuals, you’re not going to make an impact on the business. Because as you said, if they don’t use any of the outputs we make, then they really aren’t solutions and no value is created. - Brian (25:07)

“It’s really important to do what we call primary research where you’re directly interfacing as much as possible with the horse’s mouth, no third parties, no second parties. You’ve really got to develop that empathy.” - Brian (25:23)

“When we are designing some system or screen or other digital artifact, [we have to understand] this is not only digital, but a product. We have to understand people, how people interact with systems, with computers, and how people interact with visual presentations.” - João (28:16)

Links Oi: https://www.oi.com.br/ LinkedIn: https://www.linkedin.com/in/critis/ Instagram: https://www.instagram.com/critis/

The Tableau Workshop offers a comprehensive, hands-on guide to mastering data visualization with Tableau. Through practical exercises and engaging examples, you will learn how to prepare, analyze, and visualize data to uncover valuable business insights. By completing this book, you will confidently understand the key concepts and tools needed to create impactful data-driven visual stories. What this Book will help me do Master the use of Tableau Desktop and Tableau Prep for data visualization tasks. Gain the ability to prepare and process data for effective analysis. Learn to choose and utilize the most appropriate chart types for different scenarios. Develop the skills to create interactive dashboards that engage stakeholders. Understand how to perform calculations to extract deeper insights from data. Author(s) Sumit Gupta, None Pinto, Shweta Savale, JC Gillet None, and None Cherven are experts in the field of data analytics and visualization. With diverse backgrounds in business intelligence and hands-on experience with industry tools like Tableau, they bring valuable insights to this book. Their collaborative effort offers practical, real-world knowledge tailored to help learners excel in Tableau and data visualization. With their passion for making technical concepts accessible, they guide readers step by step through their learning journey. Who is it for? This book is ideal for professionals, analysts, or students looking to delve into the world of data visualization with Tableau. Whether you're a complete beginner seeking foundational knowledge, or an intermediate user aiming to refine your skills, this book offers the practical insights you need. It's designed for those who want to master Tableau tools, explore meaningful data insights, and effectively communicate them through engaging dashboards and stories.

Discover the power of Amazon QuickSight with this comprehensive guide. Learn to create stunning data visualizations, integrate machine learning insights, and automate operations to optimize your data analytics workflows. This book offers practical guidance on utilizing QuickSight to develop insightful and interactive business intelligence solutions. What this Book will help me do Understand the role of Amazon QuickSight within the AWS analytics ecosystem. Learn to configure data sources and develop visualizations effectively. Gain skills in adding interactivity to dashboards using custom controls and parameters. Incorporate machine learning capabilities into your dashboards, including forecasting and anomaly detection. Explore advanced features like QuickSight APIs and embedded multi-tenant analytics design. Author(s) None Samatas is an AWS-certified big data solutions architect with years of experience in designing and implementing scalable analytics solutions. With a clear and practical approach, None teaches how to effectively leverage Amazon QuickSight for efficient and insightful business intelligence applications. Their expertise ensures readers will gain actionable skills. Who is it for? This book is ideal for business intelligence (BI) developers and data analysts looking to deepen their expertise in creating interactive dashboards using Amazon QuickSight. It is a perfect guide for professionals aiming to explore machine learning integration in BI solutions. Familiarity with basic data visualization concepts is recommended, but no prior experience with Amazon QuickSight is needed.

Learn the core aspects of NumPy, Matplotlib, and Pandas, and use them to write programs with Python 3. This book focuses heavily on various data visualization techniques and will help you acquire expert-level knowledge of working with Matplotlib, a MATLAB-style plotting library for Python programming language that provides an object-oriented API for embedding plots into applications. You'll begin with an introduction to Python 3 and the scientific Python ecosystem. Next, you'll explore NumPy and ndarray data structures, creation routines, and data visualization. You'll examine useful concepts related to style sheets, legends, and layouts, followed by line, bar, and scatter plots. Chapters then cover recipes of histograms, contours, streamplots, and heatmaps, and how to visualize images and audio with pie and polar charts. Moving forward, you'll learn how to visualize with pcolor, pcolormesh, and colorbar, and how to visualize in 3D in Matplotlib, create simple animations, and embed Matplotlib with different frameworks. The concluding chapters cover how to visualize data with Pandas and Matplotlib, Seaborn, and how to work with the real-life data and visualize it. After reading Hands-on Matplotlib you'll be proficient with Matplotlib and able to comfortably work with ndarrays in NumPy and data frames in Pandas. What You'll Learn Understand Data Visualization and Python using Matplotlib Review the fundamental data structures in NumPy and Pandas Work with 3D plotting, visualizations, and animations Visualize images and audio data Who This Book Is For Data scientists, machine learning engineers and software professionals with basic programming skills.

Learn Tableau by working through concrete examples and issues that you are likely to face in your day-to-day work. Author Shankar Arul starts by teaching you the fundamentals of data analytics before moving on to the core concepts of Tableau. You will learn how to create calculated fields, and about the currently available calculation functionalities in Tableau, including Basic Expressions, Level of Detail (LOD) Expressions, and Table Calculations. As the book progresses, you’ll be walked through comparisons and trend calculations using tables. A concluding chapter on dashboarding will show you how to build actionable dashboards to communicate analysis and visualizations. You’ll also see how Tableau can complement and communicate with Excel. After completing this book, you will be ready to tackle the challenges of data analytics using Tableau without getting bogged down by the technicalities of the tool. What Will You Learn Master the core concepts of Tableau Automate and simplify dashboards to help business users Understand the basics of data visualization techniques Leverage powerful features such as parameters, table calculations, level of detail expressions, and more Who is This book For Business analysts, data analysts, as well as financial analysts.

Managing and Visualizing Your BIM Data is an essential guide for AEC professionals who want to harness the power of data to enhance their projects. Designed with a hands-on approach, this book delves into using Autodesk Dynamo for data collection and Microsoft Power BI for creating insightful dashboards. By the end, readers will be adept at connecting BIM models to interactive visualizations. What this Book will help me do Gain a deep understanding of data collection workflows in Autodesk Dynamo. Learn to connect Building Information Modeling (BIM) data to Power BI dashboards. Master the basics and advanced features of Dynamo for BIM data management. Create dynamic and visually appealing Power BI dashboards for AEC projects. Explore real-world use cases with expert-guided hands-on examples. Author(s) The authors, None Pellegrino, None Bottiglieri, None Crump, None Pieper, and None Touil, are experienced professionals in the AEC and software development industries. With extensive backgrounds in Building Information Modeling (BIM) and data visualization, they bring practical insights combined with a passion for teaching. Their approach ensures readers not only learn the tools but also understand the reasoning behind best practices. Who is it for? This book is ideal for BIM managers and coordinators, design technology managers, and other Architecture, Engineering, and Construction (AEC) professionals. Readers with a foundational knowledge of BIM will find it particularly beneficial for enhancing their data analysis and reporting capabilities. If you're aiming to elevate your skill set in managing BIM data and creating impactful visualizations, this guide is for you.

From a global pandemic to extreme weather, the events of 2020 and 2021 have caused organizations to make quick and constant adjustments to their strategy and operations. This transformation is likely to continue and have a major impact on analytics. Not only do responders to Experian's annual Global Data Management survey confirm more demand for data insights, but most of them also believe the lack of agility hurt their organization's responses to fast-changing business needs. With this O'Reilly report, you'll learn how organizations have begun to take new approaches to analytics for business reinvention and digital transformation. Chief analytics and data officers and data analytics, data science, data visualization leaders will explore converged analytics and find out how it differs from legacy and current analytics approaches. You'll see where your organization stands in its journey to convergence--and what you need to do next. This report helps you: Examine how three organizations in different industries and with different objectives have benefited from modern analytics Learn how analytics has evolved to support greater business agility at scale Examine the alignment of people, processes, tools, and data in converged analytics Learn the five stages of analytical competition and six dimensions for benchmarking maturity Explore practices that you can adopt to improve your analytics capabilities and your agility

Use R 4, RStudio, Tidyverse, and Shiny to interrogate and analyze your data, and then use the D3 JavaScript library to format and display that data in an elegant, informative, and interactive way. You will learn how to gather data effectively, and also how to understand the philosophy and implementation of each type of chart, so as to be able to represent the results visually. With the popularity of the R language, the art and practice of creating data visualizations is no longer the preserve of mathematicians, statisticians, or cartographers. As technology leaders, we can gather metrics around what we do and use data visualizations to communicate that information. Pro Data Visualization Using R and JavaScript combines the power of the R language with the simplicity and familiarity of JavaScript to display clear and informative data visualizations. Gathering and analyzing empirical data is the key to truly understanding anything. We can track operational metrics to quantify the health of our products in production. We can track quality metrics of our projects, and even use our data to identify bad code. Visualizing this data allows anyone to read our analysis and easily get a deep understanding of the story the data tells. This book makes the R language approachable, and promotes the idea of data gathering and analysis mostly using web interfaces. What You Will Learn Carry out data visualization using R and JavaScript Use RStudio for data visualization Harness Tidyverse data pipelines Apply D3 and R Notebooks towards your data Work with the R Plumber API generator, Shiny, and more Who This Book Is For Programmers and data scientists/analysts who have some prior experience with R and JavaScript.

"Microsoft Power BI Cookbook" is an advanced reference for professionals working with Power BI. Featuring over 90 practical, hands-on recipes, this book allows you to master Power BI for data modeling, creating dashboards, and optimizing queries. You will learn practical tips and techniques, enabling you to create effective and customized Power BI solutions for various business needs. What this Book will help me do Master advanced data cleansing and integration techniques in Power BI's Power Query Editor. Develop intuitive, efficient dashboards and reports using best practices for data visualization. Optimize performance for large datasets using aggregation tables and efficient query techniques. Implement sophisticated analysis and business logic using the power of DAX programming language. Deploy and manage Power BI solutions leveraging integration with Microsoft ecosystem tools. Author(s) Greg Deckler and None Powell are seasoned Power BI experts with extensive backgrounds in business intelligence and data solutions. Greg is a recognized Power BI consultant and author with a focus on delivering impactful BI solutions. None brings their experience in utilizing Power BI for diverse organizational needs. Together, they emphasize hands-on learning and actionable insights in their collaborative writing. Who is it for? This book is aimed at business intelligence professionals who already have a basic understanding of Power BI. Ideal readers are those seeking to deepen their knowledge of advanced features and apply best practices in their projects. Whether you're enhancing your existing Power BI skills or managing complex datasets, this book will provide the techniques and insights to excel in your role.

Join host Avery Smith on this episode of the Data Career Podcast for an exciting 'Ask Avery' session! We cover various topics, including the roles and differences between data analysts, data engineers, and data scientists, as well as transitioning careers, essential skills for data engineering, forecasting techniques, and more.

f you have questions about data visualization, Python, or breaking into data science, this episode has got you covered.

Tune in for valuable insights and professional advice to boost your data career!

Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

Whether you're a beginner just learning how to create data visualizations or a Jedi who's already used Tableau for years, this cookbook has a recipe for everyone. Author Lorna Brown provides more than 100 practical recipes to enhance the way you build Tableau dashboards--and helps you understand your data through the power of Tableau Desktop's interactive datavisualizations. With this cookbook, Tableau beginners will learn hands-on how this unique self-serve tool works, while experienced users will find this book to be an ideal reference guide on how to employ specific techniques. It also links you to online resources and community features, such as Tableau Tip Tuesday and Workout Wednesday. By the time you reach the end, you'll be a competent user of Tableau Desktop. You'll learn how to: Build both basic and complex data visualizations with Tableau Desktop Gain hands-on experience with Tableau's latest features, including set and parameter actions Create interactive dashboards to support business questions Improve your analytical skills to enhance the visualizations you've already created Learn data visualization skills and best practices to help you and your organization

Flow Immersive is the next generation of data visualization and storytelling. Sign up to be on the waitlist: https://flowimmersive.com/signup

Follow Michael DiBenigno on TikTok: https://www.tiktok.com/@the.data.guy?lang=en

Want to break into data science? Check out my new course coming out later this summer: Data Career Jumpstart - https://www.datacareerjumpstart.com

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Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

In a crowded field of data visualization and analytics tools, Tableau Desktop has emerged as the clear leader. This is partly due to its ease of use, but once you dive into Tableau's extensive feature set, you'll understand just how powerful and flexible this software can be for your business or organization. With this handy pocket reference, author Ryan Sleeper (Innovative Tableau) shows you how to translate the vast amounts of data into useful information. Tableau has done an amazing job of making valuable insights accessible to analysts and executives who would otherwise need to rely on IT. This book quickly guides you through Tableau Desktop's learning curve. You'll learn: How to shape data for use with Tableau Desktop How to create the most effective chart types Core concepts including discrete versus continuous Must-know technical features including filters, parameters, and sets Key syntax for creating the most useful analyses How to bring it all together with dashboardsAnd more!

Database developers and administrators will use this book to learn how to deploy machine learning models in Oracle Database and in Oracle’s Autonomous Database cloud offering. The book covers the technologies that make up the Oracle Machine Learning (OML) platform, including OML4SQL, OML Notebooks, OML4R, and OML4Py. The book focuses on Oracle Machine Learning as part of the Oracle Autonomous Database collaborative environment. Also covered are advanced topics such as delivery and automation pipelines. Throughout the book you will find practical details and hand-on examples showing you how to implement machine learning and automate deployment of machine learning. Discussion around the examples helps you gain a conceptual understanding of machine learning. Important concepts discussed include the methods involved, the algorithms to choose from, and mechanisms for process and deployment. Seasoned database professionals looking to make the leap into machine learning as a growth path will find much to like in this book as it helps you step up and use your current knowledge of Oracle Database to transition into providing machine learning solutions. What You Will Learn Use the Oracle Machine Learning (OML) Notebooks for data visualization and machine learning model building and evaluation Understand Oracle offerings for machine learning Develop machine learning with Oracle database using the built-in machine learning packages Develop and deploy machine learning models using OML4SQL and OML4R Leverage the Oracle Autonomous Database and its collaborative environment for Oracle Machine Learning Develop and deploy machine learning projects in Oracle Autonomous Database Build an automated pipeline that can detect and handle changes in data/model performance Who This Book Is For Database developers and administrators who want to learn about machine learning, developers who want to build models and applications using Oracle Database’s built-in machine learning feature set, and administrators tasked with supporting applications on Oracle Database that make use of the Oracle Machine Learning feature set

Integrate D3.js into a React TypeScript project and create a chart component working in harmony with React. This book will show you how utilize D3 with React to bring life to your charts. Seasoned author Elad Elrom will show you how to create simple charts such as line, bar, donut, scatter, histogram and others, and advanced charts such as a world map and force charts. You'll also learn to share the data across your components and charts using React Recoil state management. Then integrate third-party chart libraries that are built on D3 such as Rechart, Visx, Nivo, React-vi, and Victory and in the end deploy your chart as a server or serverless app on popular platforms. React and D3 are two of the most popular frameworks in their respective areas – learn to bring them together and take your storytelling to the next level. What You'll Learn Set up your project with React, TypeScript and D3.js Create simple and advanced D3.js charts Work with complex charts such as world and force charts Integrate D3 data with React state management Improve the performance of your D3 components Deploy as a server or serverless app and debug test Who This Book Is ForReaders that already have basic knowledge of React, HTML, CSS and JavaScript.

Tableau 2021 brings a wide range of tools and techniques for mastering data visualization and business intelligence. In this book, you will delve into the advanced methodologies to fully utilize Tableau's capabilities. Whether you're dealing with geo-spatial, time-series analytics, or complex dashboards, this resource provides expertise through real-world data challenges. What this Book will help me do Draw connections between multiple databases and create insightful Tableau dashboards. Master advanced data visualization techniques that lead to impactful storytelling. Understand Tableau's integration with programming languages such as Python and R. Analyze datasets with time-series and geo-spatial methods to gain predictive insights. Leverage Tableau Prep Builder for efficient data cleaning and transformation processes. Author(s) Marleen Meier and David Baldwin are seasoned professionals in business intelligence and data analytics. They bring years of practical experience and have helped numerous organizations worldwide transform their data visualization strategies using Tableau. Their collaborative approach ensures a comprehensive, beginner to advanced learning experience. Who is it for? This book is perfect for business intelligence analysts, data analysts, and industry professionals who are already familiar with Tableau's basics and wish to expand their knowledge. It provides advanced techniques and implementations of Tableau for improving data storytelling and dashboard performance. Readers seeking to connect Tableau with external programming tools will also greatly benefit from this guide.

This book, "Interactive Dashboards and Data Apps with Plotly and Dash", is a practical guide to building dynamic dashboards and applications using the Dash Python framework. It covers creating visualizations, integrating interactive controls, and deploying the apps, all without requiring JavaScript expertise. What this Book will help me do Master creating interactive data dashboards using Dash and Plotly. Understand how to integrate controls such as sliders and dropdowns into apps. Learn to use Plotly Express for visually representing data with ease. Develop capabilities to deploy a fully functional web app for data interaction. Understand how to use multi-page configurations and URLs for advanced apps. Author(s) None Dabbas is a seasoned Python developer with extensive expertise in data visualization and full-stack development. Drawing from real-world experience, None brings a practical approach to teaching, ensuring that learners understand not only how to build applications but why the approach works. Who is it for? This book is ideal for data analysts, engineers, and developers looking to enhance their visualization capabilities. If you are familiar with Python and have basic HTML skills, you will find this book accessible and rewarding. Beginners looking to explore advanced dashboard creation without JavaScript will also appreciate the clear approach.