Mastering Splunk :: optimize your machine-generated data effectively by developing advanced analytics with Splunk /
Annotation.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham, UK :
Packt Publishing,
2014.
|
| Schriftenreihe: | Professional expertise distilled.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Annotation. |
| Beschreibung: | Includes index. |
| Beschreibung: | 1 online resource (1 volume) : illustrations |
| ISBN: | 9781782173847 1782173846 |
Internformat
MARC
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| 245 | 1 | 0 | |a Mastering Splunk : |b optimize your machine-generated data effectively by developing advanced analytics with Splunk / |c James Miller. |
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing, |c 2014. | |
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| 500 | |a Includes index. | ||
| 520 | 8 | |a Annotation. |b This book is for those Splunk developers who want to learn advanced strategies to deal with big data from an enterprise architectural perspective. You need to have good working knowledge of Splunk. | |
| 505 | 0 | |a Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The Application of Splunk; The definition of Splunk; Keeping it simple; Universal file handling; Confidentiality and security; The evolution of Splunk; The Splunk approach; Conventional use cases; Investigational searching; Searching with pivot; The event timeline; Monitoring; Alerting; Reporting; Visibility in the operational world; Operational intelligence; A technology-agnostic approach; Decision support -- analysis in real time; ETL analytics and preconceptions | |
| 505 | 8 | |a The complements of SplunkODBC; Splunk -- outside the box; Customer Relationship Management; Emerging technologies; Knowledge discovery and data mining; Disaster recovery; Virus protection; The enhancement of structured data; Project management; Firewall applications; Enterprise wireless solutions; Hadoop technologies; Media measurement; Social media; Geographical Information Systems; Mobile Device Management; Splunk in action; Summary; Chapter 2: Advanced Searching; Searching in Splunk; The search dashboard; The new search dashboard; The Splunk search mechanism | |
| 505 | 8 | |a The Splunk quick reference guidePlease assist me, let me go; Basic optimization; Fast, verbose, or smart?; The breakdown of commands; Understanding the difference between sparse and dense; Searching for operators, command formats, and tags; The process flow; Boolean expressions; You can quote me, I'm escaping; Tag me Splunk!; Assigning a search tag; Tagging field-value pairs; Wild tags!; Disabling and deleting tags; Transactional searching; Knowledge management; Some working examples; Subsearching; Output settings for subsearches; Search Job Inspector; Searching with parameters | |
| 505 | 8 | |a The eval statementA simple example; Splunk macros; Creating your own macro; Using your macros; The limitations of Splunk; Search results; Some basic Splunk search examples; Additional formatting; Summary; Chapter 3: Mastering Tables, Charts, and Fields; Tables, charts, and fields; Splunking into tables; The table command; The Splunk rename command; Limits; Fields; An example of the fields command; Returning search results as charts; The chart command; The split-by fields; The where clause; More visualization examples; Some additional functions; Splunk bucketing | |
| 505 | 8 | |a Reporting using the timechart commandArguments required by the timechart command; Bucket time spans versus per_* functions; Drilldowns; The drilldown options; The basic drilldown functionality; Row drilldowns; Cell drilldowns; Chart drilldowns; Legends; Pivot; The pivot editor; Working with pivot elements; Filtering your pivots; Split; Column values; Pivot table formatting; A quick example; Sparklines; Summary; Chapter 4: Lookups; Introduction; Configuring a simple field lookup; Defining lookups in Splunk Web; Automatic lookups; The Add new page; Configuration files | |
| 505 | 8 | |a Implementing a lookup using configuration files -- an example | |
| 546 | |a English. | ||
| 650 | 0 | |a Big data. |0 http://id.loc.gov/authorities/subjects/sh2012003227 | |
| 650 | 0 | |a Data mining. |0 http://id.loc.gov/authorities/subjects/sh97002073 | |
| 650 | 0 | |a Automatic data collection systems. |0 http://id.loc.gov/authorities/subjects/sh85010095 | |
| 650 | 6 | |a Données volumineuses. | |
| 650 | 6 | |a Exploration de données (Informatique) | |
| 650 | 6 | |a Collecte automatique des données. | |
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| 776 | 0 | 8 | |i Print version: |a Miller, James. |t Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk. |d Birmingham, England : Packt Publishing, ©2014 |h ix, 321 pages |k Professional Expertise Distilled |z 9781782173830 |
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| contents | Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The Application of Splunk; The definition of Splunk; Keeping it simple; Universal file handling; Confidentiality and security; The evolution of Splunk; The Splunk approach; Conventional use cases; Investigational searching; Searching with pivot; The event timeline; Monitoring; Alerting; Reporting; Visibility in the operational world; Operational intelligence; A technology-agnostic approach; Decision support -- analysis in real time; ETL analytics and preconceptions The complements of SplunkODBC; Splunk -- outside the box; Customer Relationship Management; Emerging technologies; Knowledge discovery and data mining; Disaster recovery; Virus protection; The enhancement of structured data; Project management; Firewall applications; Enterprise wireless solutions; Hadoop technologies; Media measurement; Social media; Geographical Information Systems; Mobile Device Management; Splunk in action; Summary; Chapter 2: Advanced Searching; Searching in Splunk; The search dashboard; The new search dashboard; The Splunk search mechanism The Splunk quick reference guidePlease assist me, let me go; Basic optimization; Fast, verbose, or smart?; The breakdown of commands; Understanding the difference between sparse and dense; Searching for operators, command formats, and tags; The process flow; Boolean expressions; You can quote me, I'm escaping; Tag me Splunk!; Assigning a search tag; Tagging field-value pairs; Wild tags!; Disabling and deleting tags; Transactional searching; Knowledge management; Some working examples; Subsearching; Output settings for subsearches; Search Job Inspector; Searching with parameters The eval statementA simple example; Splunk macros; Creating your own macro; Using your macros; The limitations of Splunk; Search results; Some basic Splunk search examples; Additional formatting; Summary; Chapter 3: Mastering Tables, Charts, and Fields; Tables, charts, and fields; Splunking into tables; The table command; The Splunk rename command; Limits; Fields; An example of the fields command; Returning search results as charts; The chart command; The split-by fields; The where clause; More visualization examples; Some additional functions; Splunk bucketing Reporting using the timechart commandArguments required by the timechart command; Bucket time spans versus per_* functions; Drilldowns; The drilldown options; The basic drilldown functionality; Row drilldowns; Cell drilldowns; Chart drilldowns; Legends; Pivot; The pivot editor; Working with pivot elements; Filtering your pivots; Split; Column values; Pivot table formatting; A quick example; Sparklines; Summary; Chapter 4: Lookups; Introduction; Configuring a simple field lookup; Defining lookups in Splunk Web; Automatic lookups; The Add new page; Configuration files Implementing a lookup using configuration files -- an example |
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| discipline | Informatik |
| format | Electronic eBook |
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| indexdate | 2024-11-27T13:26:26Z |
| institution | BVB |
| isbn | 9781782173847 1782173846 |
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| series | Professional expertise distilled. |
| series2 | Professional expertise distilled |
| spelling | Miller, James D. (Software consultant), author. http://id.loc.gov/authorities/names/nb2016005442 Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / James Miller. Birmingham, UK : Packt Publishing, 2014. 1 online resource (1 volume) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier text file Professional expertise distilled Online resource; title from cover (Safari, viewed January 22, 2015). Includes index. Annotation. This book is for those Splunk developers who want to learn advanced strategies to deal with big data from an enterprise architectural perspective. You need to have good working knowledge of Splunk. Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The Application of Splunk; The definition of Splunk; Keeping it simple; Universal file handling; Confidentiality and security; The evolution of Splunk; The Splunk approach; Conventional use cases; Investigational searching; Searching with pivot; The event timeline; Monitoring; Alerting; Reporting; Visibility in the operational world; Operational intelligence; A technology-agnostic approach; Decision support -- analysis in real time; ETL analytics and preconceptions The complements of SplunkODBC; Splunk -- outside the box; Customer Relationship Management; Emerging technologies; Knowledge discovery and data mining; Disaster recovery; Virus protection; The enhancement of structured data; Project management; Firewall applications; Enterprise wireless solutions; Hadoop technologies; Media measurement; Social media; Geographical Information Systems; Mobile Device Management; Splunk in action; Summary; Chapter 2: Advanced Searching; Searching in Splunk; The search dashboard; The new search dashboard; The Splunk search mechanism The Splunk quick reference guidePlease assist me, let me go; Basic optimization; Fast, verbose, or smart?; The breakdown of commands; Understanding the difference between sparse and dense; Searching for operators, command formats, and tags; The process flow; Boolean expressions; You can quote me, I'm escaping; Tag me Splunk!; Assigning a search tag; Tagging field-value pairs; Wild tags!; Disabling and deleting tags; Transactional searching; Knowledge management; Some working examples; Subsearching; Output settings for subsearches; Search Job Inspector; Searching with parameters The eval statementA simple example; Splunk macros; Creating your own macro; Using your macros; The limitations of Splunk; Search results; Some basic Splunk search examples; Additional formatting; Summary; Chapter 3: Mastering Tables, Charts, and Fields; Tables, charts, and fields; Splunking into tables; The table command; The Splunk rename command; Limits; Fields; An example of the fields command; Returning search results as charts; The chart command; The split-by fields; The where clause; More visualization examples; Some additional functions; Splunk bucketing Reporting using the timechart commandArguments required by the timechart command; Bucket time spans versus per_* functions; Drilldowns; The drilldown options; The basic drilldown functionality; Row drilldowns; Cell drilldowns; Chart drilldowns; Legends; Pivot; The pivot editor; Working with pivot elements; Filtering your pivots; Split; Column values; Pivot table formatting; A quick example; Sparklines; Summary; Chapter 4: Lookups; Introduction; Configuring a simple field lookup; Defining lookups in Splunk Web; Automatic lookups; The Add new page; Configuration files Implementing a lookup using configuration files -- an example English. Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Automatic data collection systems. http://id.loc.gov/authorities/subjects/sh85010095 Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. COMPUTERS General. bisacsh Automatic data collection systems fast Big data fast Data mining fast has work: Mastering Splunk (Text) https://id.oclc.org/worldcat/entity/E39PCGF4rrh7hQX8GHBdkRhXQy https://id.oclc.org/worldcat/ontology/hasWork Print version: Miller, James. Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk. Birmingham, England : Packt Publishing, ©2014 ix, 321 pages Professional Expertise Distilled 9781782173830 Professional expertise distilled. http://id.loc.gov/authorities/names/no2015143013 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=929414 Volltext |
| spellingShingle | Miller, James D. (Software consultant) Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / Professional expertise distilled. Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The Application of Splunk; The definition of Splunk; Keeping it simple; Universal file handling; Confidentiality and security; The evolution of Splunk; The Splunk approach; Conventional use cases; Investigational searching; Searching with pivot; The event timeline; Monitoring; Alerting; Reporting; Visibility in the operational world; Operational intelligence; A technology-agnostic approach; Decision support -- analysis in real time; ETL analytics and preconceptions The complements of SplunkODBC; Splunk -- outside the box; Customer Relationship Management; Emerging technologies; Knowledge discovery and data mining; Disaster recovery; Virus protection; The enhancement of structured data; Project management; Firewall applications; Enterprise wireless solutions; Hadoop technologies; Media measurement; Social media; Geographical Information Systems; Mobile Device Management; Splunk in action; Summary; Chapter 2: Advanced Searching; Searching in Splunk; The search dashboard; The new search dashboard; The Splunk search mechanism The Splunk quick reference guidePlease assist me, let me go; Basic optimization; Fast, verbose, or smart?; The breakdown of commands; Understanding the difference between sparse and dense; Searching for operators, command formats, and tags; The process flow; Boolean expressions; You can quote me, I'm escaping; Tag me Splunk!; Assigning a search tag; Tagging field-value pairs; Wild tags!; Disabling and deleting tags; Transactional searching; Knowledge management; Some working examples; Subsearching; Output settings for subsearches; Search Job Inspector; Searching with parameters The eval statementA simple example; Splunk macros; Creating your own macro; Using your macros; The limitations of Splunk; Search results; Some basic Splunk search examples; Additional formatting; Summary; Chapter 3: Mastering Tables, Charts, and Fields; Tables, charts, and fields; Splunking into tables; The table command; The Splunk rename command; Limits; Fields; An example of the fields command; Returning search results as charts; The chart command; The split-by fields; The where clause; More visualization examples; Some additional functions; Splunk bucketing Reporting using the timechart commandArguments required by the timechart command; Bucket time spans versus per_* functions; Drilldowns; The drilldown options; The basic drilldown functionality; Row drilldowns; Cell drilldowns; Chart drilldowns; Legends; Pivot; The pivot editor; Working with pivot elements; Filtering your pivots; Split; Column values; Pivot table formatting; A quick example; Sparklines; Summary; Chapter 4: Lookups; Introduction; Configuring a simple field lookup; Defining lookups in Splunk Web; Automatic lookups; The Add new page; Configuration files Implementing a lookup using configuration files -- an example Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Automatic data collection systems. http://id.loc.gov/authorities/subjects/sh85010095 Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. COMPUTERS General. bisacsh Automatic data collection systems fast Big data fast Data mining fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2012003227 http://id.loc.gov/authorities/subjects/sh97002073 http://id.loc.gov/authorities/subjects/sh85010095 |
| title | Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / |
| title_auth | Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / |
| title_exact_search | Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / |
| title_full | Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / James Miller. |
| title_fullStr | Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / James Miller. |
| title_full_unstemmed | Mastering Splunk : optimize your machine-generated data effectively by developing advanced analytics with Splunk / James Miller. |
| title_short | Mastering Splunk : |
| title_sort | mastering splunk optimize your machine generated data effectively by developing advanced analytics with splunk |
| title_sub | optimize your machine-generated data effectively by developing advanced analytics with Splunk / |
| topic | Big data. http://id.loc.gov/authorities/subjects/sh2012003227 Data mining. http://id.loc.gov/authorities/subjects/sh97002073 Automatic data collection systems. http://id.loc.gov/authorities/subjects/sh85010095 Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. COMPUTERS General. bisacsh Automatic data collection systems fast Big data fast Data mining fast |
| topic_facet | Big data. Data mining. Automatic data collection systems. Données volumineuses. Exploration de données (Informatique) Collecte automatique des données. COMPUTERS General. Automatic data collection systems Big data Data mining |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=929414 |
| work_keys_str_mv | AT millerjamesd masteringsplunkoptimizeyourmachinegenerateddataeffectivelybydevelopingadvancedanalyticswithsplunk |