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Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights  Cover Image E-book E-book

Splunk 7 essentials : demystify machine data by leveraging datasets, building reports, and sharing powerful insights

Contreras, J-P (author.). Delgado, Erickson, (author.). Sigman, Betsy Page, (author.).

Summary: Transform machine data into powerful analytical intelligence using Splunk Key Features Analyze and visualize machine data to step into the world of Splunk! Leverage the exceptional analysis and visualization capabilities to make informed decisions for your business This easy-to-follow, practical book can be used by anyone - even if you have never managed data before Book Description Splunk is a search, reporting, and analytics software platform for machine data, which has an ever-growing market adoption rate. More organizations than ever are adopting Splunk to make informed decisions in areas such as IT operations, information security, and the Internet of Things. The first two chapters of the book will get you started with a simple Splunk installation and set up of a sample machine data generator, called Eventgen. After this, you will learn to create various reports, dashboards, and alerts. You will also explore Splunk's Pivot functionality to model data for business users. You will then have the opportunity to test-drive Splunk's powerful HTTP Event Collector. After covering the core Splunk functionality, you'll be provided with some real-world best practices for using Splunk, and information on how to build upon what you've learned in this book. Throughout the book, there will be additional comments and best practice recommendations from a member of the SplunkTrust Community, called "Tips from the Fez". What you will learn Install and configure Splunk for personal use Store event data in Splunk indexes, classify events into sources, and add data fields Learn essential Splunk Search Processing Language commands and best practices Create powerful real-time or user-input dashboards Be proactive by implementing alerts and scheduled reports Tips from the Fez: best practices using Splunk features and add-ons Understand security and deployment considerations for taking Splunk to an organizational level Who this book is for This book is for the beginners who want to get well versed in the services offered by Splunk 7. If you want to be a data/business analyst or want to be a system administrator, this book is what you want. No prior knowledge of Splunk is required

Record details

  • ISBN: 9781788839112
  • ISBN: 9781788830126
  • ISBN: 1788830121
  • Physical Description: 1 online resource (1 volume) : illustrations
    remote
    Computer data.
  • Edition: Third edition.
  • Publisher: Birmingham, UK : Packt Publishing, 2018.

Content descriptions

General Note:
CatMonthString.january.24
Multi-User.
Bibliography, etc. Note: Includes bibliographical references.
Formatted Contents Note: Splunk and big dataStreaming data; Analytical data latency; Sparseness of data; Splunk data sources; Machine data; Web logs; Data files; Social media data; Relational database data; Other data types; Creating indexes; Buckets; Log files as data input; Splunk events and fields; Extracting new fields; Summary; Chapter 3: Search Processing Language; Anatomy of a search; Search pipeline; Time modifiers; Filtering search results; Search command -- stats; Search command -- top/rare; Search commands -- chart and timechart; Search command -- eval; Search command -- rex; Summary.
Type of Computer File or Data Note:
Text (HTML), electronic book.
System Details Note:
Mode of access: Internet.
Terms Governing Use and Reproduction Note:
Access requires VIU IP addresses and is restricted to VIU students, faculty and staff.
Access restricted by subscription.
Issuing Body Note:
Made available online by EBSCO.
Source of Description Note:
Online resource; title from digital title page (viewed on July 29, 2019).
Subject: Multi-User.
Operational research
Information architecture
Enterprise software
Database design & theory
Data mining
Data capture & analysis
Computers -- Enterprise Applications -- Business Intelligence Tools
Computers -- Data Processing
Computers -- Data Modeling & Design
Big data
Automatic data collection systems
Exploration de donn�ees (Informatique)
Donn�ees volumineuses
Collecte automatique des donn�ees
Data Mining
Data mining
Big data
Automatic data collection systems

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