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Splunk Operational Intelligence Cookbook

You're reading from   Splunk Operational Intelligence Cookbook Over 80 recipes for transforming your data into business-critical insights using Splunk

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Product type Paperback
Published in May 2018
Publisher
ISBN-13 9781788835237
Length 541 pages
Edition 3rd Edition
Languages
Tools
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Authors (4):
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Yogesh Raheja Yogesh Raheja
Author Profile Icon Yogesh Raheja
Yogesh Raheja
Josh Diakun Josh Diakun
Author Profile Icon Josh Diakun
Josh Diakun
Derek Mock Derek Mock
Author Profile Icon Derek Mock
Derek Mock
Paul R. Johnson Paul R. Johnson
Author Profile Icon Paul R. Johnson
Paul R. Johnson
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Toc

Table of Contents (12) Chapters Close

Preface 1. Play Time – Getting Data In 2. Diving into Data – Search and Report FREE CHAPTER 3. Dashboards and Visualizations - Make Data Shine 4. Building an Operational Intelligence Application 5. Extending Intelligence – Datasets, Modeling and Pivoting 6. Diving Deeper – Advanced Searching, Machine Learning and Predictive Analytics 7. Enriching Data – Lookups and Workflows 8. Being Proactive – Creating Alerts 9. Speeding Up Intelligence – Data Summarization 10. Above and Beyond – Customization, Web Framework, HTTP Event Collector, REST API, and SDKs 11. Other Books You May Enjoy

Calculating an hourly count of sessions versus completed transactions

From an operational intelligence standpoint, it is interesting to understand how many visitors we have to our online store and how many of these people actually purchase something. For example, if we have 1,000 people visiting a day, and only 10 people actually purchase something, this might indicate something is not quite right. Perhaps the prices of our products are too high, or the site might be difficult to use and thus needs a redesign. This information can also be used to indicate peak purchasing times.

In this first recipe, we will leverage summary indexing to understand how many sessions we have per hour versus how many actual completed purchase transactions there have been. We will plot these on a line graph going back the last 24 hours.

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