QlikView :: Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch /
QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and presen...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | , , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham :
Packt Publishing Ltd,
2018.
|
| Schriftenreihe: | Learning path.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and present it as impactful and engaging visualizations. |
| Beschreibung: | Using IntervalMatch with SCDs. |
| Beschreibung: | 1 online resource (787 pages) |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 1789954177 9781789954173 |
Internformat
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| 100 | 1 | |a García, Miguel Ángel. | |
| 245 | 1 | 0 | |a QlikView : |b Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / |c Miguel Ángel García, Barry Harmsen, Stephen Redmond, Karl Pover. |
| 260 | |a Birmingham : |b Packt Publishing Ltd, |c 2018. | ||
| 300 | |a 1 online resource (787 pages) | ||
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| 490 | 1 | |a Learning Path | |
| 588 | 0 | |a Print version record. | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Cover; Title Page; Copyright; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Performance Tuning and Scalability; Reviewing basic performance tuning techniques; Removing unneeded data; Reducing the number of rows; Reducing the number of columns; Replacing text keys with numbers; Resolving synthetic keys; Reviewing the basics; Generating test data; Generating dimension values; Generating fact table rows; Understanding how QlikView stores its data; A great primer; Looking at things from a simple level; Exporting the memory statistics for a document. | |
| 505 | 8 | |a Strategies to reduce the data size and improve performanceOptimizing field values and keys; Optimizing data by removing keys using ApplyMap; Optimizing performance by removing keys by joining tables; Optimizing memory by removing low cardinality fields; Testing chart performance for different load options; Turning the cache off; Examining the chart calculation time for different scenarios; Optimizing performance by creating counter fields; Optimizing performance by combining fact tables?; Optimizing your numbers; Optimizing chart calculation times; The QlikView calculation engine. | |
| 505 | 8 | |a Creating flags for well-known conditionsSorting for well-known conditions; Using Direct Discovery; Direct Discovery restrictions; Direct Discovery syntax; Looking at an example Direct Query; Testing scalability with JMeter; Obtaining the scalability tools; Installing JMeter; Installing the scalability tools; About the scalability tools; Running an example execution; Summary; Chapter 2: QlikView Data Modeling; Reviewing basic data modeling; Associating data; Automatically associating tables; Understanding synthetic keys; Creating composite keys. | |
| 505 | 8 | |a Realizing that facts are calculated at the level of their tableJoining data; Understanding Join and Keep; Concatenating rows; Reviewing Concatenate; Mapping data with ApplyMap; Reviewing the basic functionality of ApplyMap; Mapping numbers; Dimensional data modeling; Differentiating between facts and dimensions; Understanding the grain; Understanding star schemas; Summing with facts; Discovering more about facts; Transaction fact tables; Periodic snapshot fact tables; Factless fact tables; Dealing with nulls in fact tables in QlikView; Designing dimension tables. | |
| 505 | 8 | |a Denormalizing dimensions and conformed dimensionsUnderstanding surrogate keys; Dealing with missing or late arriving dimension values; Defining Kimball's four-step dimensional design process; Selecting the business process; Declaring the grain; Identifying the dimensions; Identifying the facts; Learning some useful reusable dimension methods; Creating a calendar dimension; Unwrapping hierarchies; Creating parent associations with HierarchyBelongsTo; Creating dimensional facts; Handling slowly changing dimensions; Taking the most recently changed record using FirstSortedValue. | |
| 500 | |a Using IntervalMatch with SCDs. | ||
| 520 | |a QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and present it as impactful and engaging visualizations. | ||
| 650 | 0 | |a Information visualization. |0 http://id.loc.gov/authorities/subjects/sh2002000243 | |
| 650 | 0 | |a Business intelligence |x Computer programs. | |
| 650 | 0 | |a Visual analytics. |0 http://id.loc.gov/authorities/subjects/sh2007004134 | |
| 650 | 6 | |a Visualisation de l'information. | |
| 650 | 6 | |a Analyse visuelle. | |
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| 650 | 7 | |a COMPUTERS |x Data Visualization. |2 bisacsh | |
| 650 | 7 | |a Information visualization |2 fast | |
| 650 | 7 | |a Visual analytics |2 fast | |
| 700 | 1 | |a Harmsen, Barry. | |
| 700 | 1 | |a Redmond, Stephen. | |
| 700 | 1 | |a Pover, Karl. | |
| 758 | |i has work: |a QlikView, advanced data visualization (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGXPhVGpCXYcR7dF8KtqHy |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
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| author | García, Miguel Ángel |
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| contents | Cover; Title Page; Copyright; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Performance Tuning and Scalability; Reviewing basic performance tuning techniques; Removing unneeded data; Reducing the number of rows; Reducing the number of columns; Replacing text keys with numbers; Resolving synthetic keys; Reviewing the basics; Generating test data; Generating dimension values; Generating fact table rows; Understanding how QlikView stores its data; A great primer; Looking at things from a simple level; Exporting the memory statistics for a document. Strategies to reduce the data size and improve performanceOptimizing field values and keys; Optimizing data by removing keys using ApplyMap; Optimizing performance by removing keys by joining tables; Optimizing memory by removing low cardinality fields; Testing chart performance for different load options; Turning the cache off; Examining the chart calculation time for different scenarios; Optimizing performance by creating counter fields; Optimizing performance by combining fact tables?; Optimizing your numbers; Optimizing chart calculation times; The QlikView calculation engine. Creating flags for well-known conditionsSorting for well-known conditions; Using Direct Discovery; Direct Discovery restrictions; Direct Discovery syntax; Looking at an example Direct Query; Testing scalability with JMeter; Obtaining the scalability tools; Installing JMeter; Installing the scalability tools; About the scalability tools; Running an example execution; Summary; Chapter 2: QlikView Data Modeling; Reviewing basic data modeling; Associating data; Automatically associating tables; Understanding synthetic keys; Creating composite keys. Realizing that facts are calculated at the level of their tableJoining data; Understanding Join and Keep; Concatenating rows; Reviewing Concatenate; Mapping data with ApplyMap; Reviewing the basic functionality of ApplyMap; Mapping numbers; Dimensional data modeling; Differentiating between facts and dimensions; Understanding the grain; Understanding star schemas; Summing with facts; Discovering more about facts; Transaction fact tables; Periodic snapshot fact tables; Factless fact tables; Dealing with nulls in fact tables in QlikView; Designing dimension tables. Denormalizing dimensions and conformed dimensionsUnderstanding surrogate keys; Dealing with missing or late arriving dimension values; Defining Kimball's four-step dimensional design process; Selecting the business process; Declaring the grain; Identifying the dimensions; Identifying the facts; Learning some useful reusable dimension methods; Creating a calendar dimension; Unwrapping hierarchies; Creating parent associations with HierarchyBelongsTo; Creating dimensional facts; Handling slowly changing dimensions; Taking the most recently changed record using FirstSortedValue. |
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| series2 | Learning Path |
| spelling | García, Miguel Ángel. QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / Miguel Ángel García, Barry Harmsen, Stephen Redmond, Karl Pover. Birmingham : Packt Publishing Ltd, 2018. 1 online resource (787 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Learning Path Print version record. Includes bibliographical references and index. Cover; Title Page; Copyright; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Performance Tuning and Scalability; Reviewing basic performance tuning techniques; Removing unneeded data; Reducing the number of rows; Reducing the number of columns; Replacing text keys with numbers; Resolving synthetic keys; Reviewing the basics; Generating test data; Generating dimension values; Generating fact table rows; Understanding how QlikView stores its data; A great primer; Looking at things from a simple level; Exporting the memory statistics for a document. Strategies to reduce the data size and improve performanceOptimizing field values and keys; Optimizing data by removing keys using ApplyMap; Optimizing performance by removing keys by joining tables; Optimizing memory by removing low cardinality fields; Testing chart performance for different load options; Turning the cache off; Examining the chart calculation time for different scenarios; Optimizing performance by creating counter fields; Optimizing performance by combining fact tables?; Optimizing your numbers; Optimizing chart calculation times; The QlikView calculation engine. Creating flags for well-known conditionsSorting for well-known conditions; Using Direct Discovery; Direct Discovery restrictions; Direct Discovery syntax; Looking at an example Direct Query; Testing scalability with JMeter; Obtaining the scalability tools; Installing JMeter; Installing the scalability tools; About the scalability tools; Running an example execution; Summary; Chapter 2: QlikView Data Modeling; Reviewing basic data modeling; Associating data; Automatically associating tables; Understanding synthetic keys; Creating composite keys. Realizing that facts are calculated at the level of their tableJoining data; Understanding Join and Keep; Concatenating rows; Reviewing Concatenate; Mapping data with ApplyMap; Reviewing the basic functionality of ApplyMap; Mapping numbers; Dimensional data modeling; Differentiating between facts and dimensions; Understanding the grain; Understanding star schemas; Summing with facts; Discovering more about facts; Transaction fact tables; Periodic snapshot fact tables; Factless fact tables; Dealing with nulls in fact tables in QlikView; Designing dimension tables. Denormalizing dimensions and conformed dimensionsUnderstanding surrogate keys; Dealing with missing or late arriving dimension values; Defining Kimball's four-step dimensional design process; Selecting the business process; Declaring the grain; Identifying the dimensions; Identifying the facts; Learning some useful reusable dimension methods; Creating a calendar dimension; Unwrapping hierarchies; Creating parent associations with HierarchyBelongsTo; Creating dimensional facts; Handling slowly changing dimensions; Taking the most recently changed record using FirstSortedValue. Using IntervalMatch with SCDs. QlikView is one of the most flexible and powerful business intelligence platforms around, and if you want to transform data into insights, it is one of the best options you have at hand. Use this Learning Path, to explore the many features of QlikView to realize the potential of your data and present it as impactful and engaging visualizations. Information visualization. http://id.loc.gov/authorities/subjects/sh2002000243 Business intelligence Computer programs. Visual analytics. http://id.loc.gov/authorities/subjects/sh2007004134 Visualisation de l'information. Analyse visuelle. REFERENCE Questions & Answers. bisacsh COMPUTERS Data Visualization. bisacsh Information visualization fast Visual analytics fast Harmsen, Barry. Redmond, Stephen. Pover, Karl. has work: QlikView, advanced data visualization (Text) https://id.oclc.org/worldcat/entity/E39PCGXPhVGpCXYcR7dF8KtqHy https://id.oclc.org/worldcat/ontology/hasWork Print version: García, Miguel Ángel. QlikView: Advanced Data Visualization. Birmingham : Packt Publishing Ltd, ©2018 9781789955996 Learning path. http://id.loc.gov/authorities/names/no2018038408 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1991791 Volltext |
| spellingShingle | García, Miguel Ángel QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / Learning path. Cover; Title Page; Copyright; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Performance Tuning and Scalability; Reviewing basic performance tuning techniques; Removing unneeded data; Reducing the number of rows; Reducing the number of columns; Replacing text keys with numbers; Resolving synthetic keys; Reviewing the basics; Generating test data; Generating dimension values; Generating fact table rows; Understanding how QlikView stores its data; A great primer; Looking at things from a simple level; Exporting the memory statistics for a document. Strategies to reduce the data size and improve performanceOptimizing field values and keys; Optimizing data by removing keys using ApplyMap; Optimizing performance by removing keys by joining tables; Optimizing memory by removing low cardinality fields; Testing chart performance for different load options; Turning the cache off; Examining the chart calculation time for different scenarios; Optimizing performance by creating counter fields; Optimizing performance by combining fact tables?; Optimizing your numbers; Optimizing chart calculation times; The QlikView calculation engine. Creating flags for well-known conditionsSorting for well-known conditions; Using Direct Discovery; Direct Discovery restrictions; Direct Discovery syntax; Looking at an example Direct Query; Testing scalability with JMeter; Obtaining the scalability tools; Installing JMeter; Installing the scalability tools; About the scalability tools; Running an example execution; Summary; Chapter 2: QlikView Data Modeling; Reviewing basic data modeling; Associating data; Automatically associating tables; Understanding synthetic keys; Creating composite keys. Realizing that facts are calculated at the level of their tableJoining data; Understanding Join and Keep; Concatenating rows; Reviewing Concatenate; Mapping data with ApplyMap; Reviewing the basic functionality of ApplyMap; Mapping numbers; Dimensional data modeling; Differentiating between facts and dimensions; Understanding the grain; Understanding star schemas; Summing with facts; Discovering more about facts; Transaction fact tables; Periodic snapshot fact tables; Factless fact tables; Dealing with nulls in fact tables in QlikView; Designing dimension tables. Denormalizing dimensions and conformed dimensionsUnderstanding surrogate keys; Dealing with missing or late arriving dimension values; Defining Kimball's four-step dimensional design process; Selecting the business process; Declaring the grain; Identifying the dimensions; Identifying the facts; Learning some useful reusable dimension methods; Creating a calendar dimension; Unwrapping hierarchies; Creating parent associations with HierarchyBelongsTo; Creating dimensional facts; Handling slowly changing dimensions; Taking the most recently changed record using FirstSortedValue. Information visualization. http://id.loc.gov/authorities/subjects/sh2002000243 Business intelligence Computer programs. Visual analytics. http://id.loc.gov/authorities/subjects/sh2007004134 Visualisation de l'information. Analyse visuelle. REFERENCE Questions & Answers. bisacsh COMPUTERS Data Visualization. bisacsh Information visualization fast Visual analytics fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh2002000243 http://id.loc.gov/authorities/subjects/sh2007004134 |
| title | QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / |
| title_auth | QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / |
| title_exact_search | QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / |
| title_full | QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / Miguel Ángel García, Barry Harmsen, Stephen Redmond, Karl Pover. |
| title_fullStr | QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / Miguel Ángel García, Barry Harmsen, Stephen Redmond, Karl Pover. |
| title_full_unstemmed | QlikView : Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / Miguel Ángel García, Barry Harmsen, Stephen Redmond, Karl Pover. |
| title_short | QlikView : |
| title_sort | qlikview advanced data visualization discover deeper insights with qlikview by building your own rich analytical applications from scratch |
| title_sub | Advanced Data Visualization : Discover Deeper Insights with Qlikview by Building Your Own Rich Analytical Applications from Scratch / |
| topic | Information visualization. http://id.loc.gov/authorities/subjects/sh2002000243 Business intelligence Computer programs. Visual analytics. http://id.loc.gov/authorities/subjects/sh2007004134 Visualisation de l'information. Analyse visuelle. REFERENCE Questions & Answers. bisacsh COMPUTERS Data Visualization. bisacsh Information visualization fast Visual analytics fast |
| topic_facet | Information visualization. Business intelligence Computer programs. Visual analytics. Visualisation de l'information. Analyse visuelle. REFERENCE Questions & Answers. COMPUTERS Data Visualization. Information visualization Visual analytics |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1991791 |
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