What this book covers

Chapter 1, Meet Hunk, covers Hunk and its basic features. Hunk is a full-featured platform to rapidly explore, analyze, and visualize data in Hadoop and the NoSQL data stores. You will learn how to install and configure Hunk. Moreover, you will learn about Hunk's architecture and Hunk Virtual Index. You will also be introduced to loading data into Hadoop in order to aid its discovery by Hunk.

Chapter 2, Explore Hadoop Data with Hunk, talks about how you can easily analyze and visualize data using the Splunk search processing language (SPL). Getting a large amount of data into Hadoop is easy but getting analytics from this data is the challenge. You will learn about the use cases of big data analytics and the security aspect of Hunk.

Chapter 3, Meet Hunk Features, teaches you about Hunk's knowledge objects. Hunk is a powerful big data analytics platform, which gives us many tools in order to explore, analyze, and visualize big data. You will learn how to build a semantic layer on top of Hadoop and discover data using the friendly user interface of Hunk Pivot.

Chapter 4, Adding Speed to Reports, covers the techniques related to report acceleration. Hunk is an extremely powerful tool and can handle a vast amount of data. However, business decisions, which depend on fresh data, can't wait.

Chapter 5, Customizing Hunk, introduces REST API, SDK, and so on. Sometimes, we want to get out of the box or need to meet business expectations and are restricted by the initial functionality. Thus, you will learn how to create customized visualization, and you will also be introduced to the Splunk Web Framework.

Chapter 6, Discovering Hunk Integration Apps, introduces you to Hunk's apps that can easily integrate with the NoSQL data stores, such as MongoDB or Sqqrl. Hunk is a universal big data analytics platform, which can easy explore data in Hadoop or the NoSQL data stores. You will learn how to connect MongoDB and explore data in its data store.

Chapter 7, Exploring Data in the Cloud, shows you how to analyze data in AWS Cloud. Some big organizations prefer to store their big data on the cloud because it gives them many benefits.