Preface

Seven years ago, I stumbled upon Elasticsearch – not as a technical instructor but as a wide-eyed data detective. It was after that I discovered Kibana; I was captivated by its ability to transform cold, numerical figures into vibrant stories, each query a brushstroke painting the canvas of insights. As I delved deeper, its power to democratize data analysis, making it accessible not just to elite statisticians but to anyone with a curious mind, ignited a passion within me.

This passion led me to the world of official Kibana 8 training, where I witnessed firsthand the transformative impact it had on individuals and organizations. But a nagging feeling persisted – the existing resources, while comprehensive, felt like dense tomes for seasoned explorers, leaving newcomers lost in the wilderness of data.

That’s where the seed of this book was sown. I envisioned a guide that didn’t just explain the “what” and “how” of Kibana but also captured the “why.” I wanted to translate the magic I saw in classrooms onto the page, making Kibana not just a tool but a bridge to a world of data-driven discovery.

Researching this book wasn’t just about combing through documentation and tutorials; it was about reliving the journey of my students. I revisited the challenges they faced, the “aha!” moments they experienced, and the questions that lingered long after the training ended. I talked to data enthusiasts, industry experts, and fellow Kibana instructors, gathering their insights and weaving them into a tapestry of practical knowledge.

Each chapter became a brushstroke on the canvas of my vision. I crafted exercises that mirrored real-world scenarios, using familiar datasets to make the learning process relatable and engaging. I translated complex concepts into digestible language, using humor and anecdotes to keep the journey as enjoyable as it is informative.

This book is more than just a compilation of Kibana functionalities; it’s an invitation to embark on a data-driven adventure. It’s for the curious mind, the aspiring analyst, or anyone who wants to unlock the secrets hidden within their data. It’s my way of sharing the magic I witnessed, igniting that spark of data passion in others, and guiding them on their own journey from data novice to empowered data detective.

Ready to transform raw data into captivating stories? This book is your Rosetta Stone, unlocking the power of Kibana 8.x. Delve into Discover, craft visual symphonies with dashboards, and unveil hidden patterns with Machine Learning (ML) and Time Series Visual Builder (TSVB). Master ES|QL’s precise sculpting, bend data with dynamic runtime fields, and learn to manage your domain with ease. Let Kibana be your data maestro, conducting insights with elegance and precision. Now, turn the page and let the analysis begin!

Who this book is for

Calling all data curious, analysis enthusiasts, and visualization voyagers! Whether you’re a seasoned data wrangler or a wide-eyed newbie, this book welcomes you with open arms (and dashboards!). This book is your launchpad to unlock the power of Kibana, the interactive data visualization platform that transforms raw numbers into captivating stories. If you’re hungry to explore hidden patterns, unearth trends from your data, and paint vibrant pictures of insights, then this guide is your compass. Whether you’re a marketer charting customer journeys, an IT whiz troubleshooting server logs, or a scientist diving into research findings, Kibana has a seat for you at its analysis table. So, ditch the spreadsheets and dive into the dynamic world of data visualization – we’ll start with baby steps and soon have you dancing with dashboards.

What this book covers

Chapter 1, Introduction to Kibana, unlocks the power of Kibana by diving into the vibrant world of data visualization. This chapter lays the foundation, introducing you to Kibana – an interactive platform that transforms raw data into captivating stories. You’ll learn its purpose, its core features, and why it’s the go-to tool for data explorers. Moreover, you will be guided through the exciting process of setting up your own Kibana environment, from installing and configuring the software to connecting it to your data source.

Chapter 2, Creating Data Views and Introducing Spaces, unlocks two powerful features that elevate your analysis game. You’ll be guided through crafting tailored data views and personalized dashboards that focus on specific aspects of your data, letting you zero in on critical insights by creating a data view that helps you select and work on a specific type of data in Kibana. Then, you will be prepared to explore the revolutionary concept of Kibana spaces. This chapter unlocks doors to efficient data sharing, streamlined workflows, and a world where collaboration takes center stage.

Chapter 3, Discovering Data through Discover, equips you with the tools to explore your datasets like a seasoned detective, sifting through raw information to uncover hidden patterns and unveil compelling insights. You’ll master the powerful search bar, unleashing precise queries to pinpoint specific data points. You’ll learn the Kibana Query Language to search through your data and also create filters. You’ll see how Discover helps us explore the data before you begin your analytics journey on your dataset.

Chapter 4, How About We Visualize?, unlocks the visual language of data in Kibana, transforming cold numbers into captivating stories. Forget static spreadsheets – here, you’ll wield diverse charts and graphs like magic wands, revealing hidden patterns and trends within your information. You’ll get to explore the power of bar charts, line graphs, and heatmaps, learning how each Lens editing tool paints a unique picture of your data’s essence. You’ll master the art of selecting the right visual for the job, ensuring your insights resonate with clarity and impact.

Chapter 5, Powering Visualizations with Near-Real-Time Updates, dives into the exciting world of near real-time data visualization with TSVB. You’ll learn to craft visualizations that update seamlessly as new information flows in, revealing hidden patterns and trends as they unfold. You get to explore TSVB’s powerful features, such as expressions, aggregations, and bucket scripting, empowering you to transform raw data into captivating stories that update with the pulse of your live systems.

Chapter 6, Data Analysis with Machine Learning, will delve into the exciting realm of ML within Kibana. Imagine using data patterns and algorithms to uncover hidden insights, predict trends, and automate anomaly detection. You’ll get to explore tools such as anomaly detection, outlier analysis, and even supervised learning, all within your familiar Kibana interface. It is a powerful fusion of data analysis and ML, unlocking a whole new layer of understanding and actionable insights from your data.

Chapter 7, Graph Visualization, will help you learn to untangle the web of your data! This chapter equips you with the power of graphs to unveil hidden connections, trace relationships, and spot patterns lurking beneath the surface of numbers.

Chapter 8, Finally, the Dashboard, teaches you how to transform raw data into visually captivating dashboards that tell a clear and compelling story. You will craft interactive layouts, weave together powerful visualizations, and apply custom filters to empower anyone to explore and understand your data with ease. This is where information comes alive, guiding informed decisions and sparking insightful conversations.

Chapter 9, ES|QL and Advanced Kibana Concepts, explores the power of data manipulation where you dive into ES|QL, crafting custom Elasticsearch queries to sculpt your insights. You will unleash runtime fields, dynamically generating data points for deeper analysis on the fly. Finally, you will master advanced Kibana settings to understand how to fine-tune your environment for maximum visual impact and intuitive exploration.

Chapter 10, Query DSL and Management through Kibana, takes a deep dive into the pulse of your data with Query DSL. You will craft precise searches, sculpt results, and bend information to your will. We’ll explore Kibana’s data management tools, keeping your information kingdom organized and secure. Prepare to master both precision and control, one query and setting at a time!

Disclaimer:

This book, Kibana 8. x: A Quick Start Guide to Data Analysis, is not sponsored, endorsed, or affiliated with Elastic NV ("Elastic") or any of its subsidiaries or affiliates. The contributors to this book are independent authors and are not acting on behalf of or as representatives of, Elastic in any capacity. The content of this book is solely the responsibility of the authors and does not necessarily reflect the views or opinions of Elastic. Elastic makes no representations or warranties of any kind, express or implied, regarding the accuracy, completeness, or timeliness of the content of this book.

To get the most out of this book

It is recommended to have a basic understanding of data. Familiarity with data types, structures, and concepts will ease navigation through Kibana’s data manipulation tools.

Some SQL knowledge is useful. While not essential, basic SQL skills can come in handy for writing simple queries in ES|QL, Kibana’s query language.

Conceptual know-how on downloading, installing, and configuring Kibana and working with YAML files is essential.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Download the example code files

You can download the example code files for this book from GitHub at https://github.com/PacktPublishing/Kibana-8.x-A-Quick-Start-Guide-to-Data-Analysis. If there’s an update to the code, it will be updated in the GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “For example, GET _ml/info will simply return the result of the current machine learning jobs on the cluster.”

A block of code is set as follows:

GET _ml/memory/<node_id>/_stats
GET _ml/memory/_stats

Any command-line input or output is written as follows:

<iframe src="https://juxwycstgeesmshyp-xxxxxxxxxxx.rp.strigo.io/app/r/s/xAwTf" height="600" width="800"></iframe>

Bold: Indicates a new term, an important word, or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “Inside the Documents layer, select data view/Index pattern you wish to work on and the Geospatial field, and then click on Add layer at the bottom.”

Tips or important notes

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