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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
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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
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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

Backfilling the number of purchases by city

In the previous recipe, you generated an hourly summary and then, after waiting for 24 hours, you were able to report on the summary data over a 24-hour period. However, what if you wanted to report over the past 30 days or even 3 months? You would have to wait a long time for your summary data to build up over time. A better way is to backfill the summary data over an earlier time period, assuming you have raw data for this time period in Splunk.

In this recipe, you will create a search that identifies the number of purchases by city on a given day, and write this search to a summary index. You will leverage the IP location database built into Splunk to obtain the city based on the IP address in the results. You will then execute a script that comes bundled with Splunk in order to backfill the summary for the previous 30 days. Following...

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