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Splunk Operational Intelligence Cookbook

Splunk Operational Intelligence Cookbook

By : Josh Diakun, Raheja, Paul R. Johnson, Derek Mock
4.7 (3)
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Splunk Operational Intelligence Cookbook

Splunk Operational Intelligence Cookbook

4.7 (3)
By: Josh Diakun, Raheja, Paul R. Johnson, Derek Mock

Overview of this book

Splunk makes it easy for you to take control of your data, and with Splunk Operational Cookbook, you can be confident that you are taking advantage of the Big Data revolution and driving your business with the cutting edge of operational intelligence and business analytics. With more than 80 recipes that demonstrate all of Splunk’s features, not only will you find quick solutions to common problems, but you’ll also learn a wide range of strategies and uncover new ideas that will make you rethink what operational intelligence means to you and your organization. You’ll discover recipes on data processing, searching and reporting, dashboards, and visualizations to make data shareable, communicable, and most importantly meaningful. You’ll also find step-by-step demonstrations that walk you through building an operational intelligence application containing vital features essential to understanding data and to help you successfully integrate a data-driven way of thinking in your organization. Throughout the book, you’ll dive deeper into Splunk, explore data models and pivots to extend your intelligence capabilities, and perform advanced searching with machine learning to explore your data in even more sophisticated ways. Splunk is changing the business landscape, so make sure you’re taking advantage of it.
Table of Contents (12 chapters)
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Using a bar chart to show the average amount spent by category

Throughout this chapter, you have been building visualizations to provide insight into the operational performance of our e-commerce website. It can also be useful to understand the customer's view and the factors that might drive them to the website. This type of information is traditionally most useful for product or marketing folks. However, it can also be useful to gain an understanding of whether an item is increasing in popularity and/or if this could ultimately lead to additional customers and heavier load on the site.

In this recipe, you will write a Splunk search to calculate the average amount of money spent, split out by product category. You will then graphically present this data using a bar chart on a new Product Monitoring dashboard.

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