Advanced analytics with Transact-SQL : exploring hidden patterns and rules in your data / / Dejan Sarka |
Autore | Sarka Dejan |
Pubbl/distr/stampa | [Place of publication not identified] : , : Apress, , [2021] |
Descrizione fisica | 1 online resource (308 pages) |
Disciplina | 005.7 |
Soggetto topico |
Big data
Business intelligence - Data processing SQL (Computer program language) |
ISBN | 1-4842-7173-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910495206103321 |
Sarka Dejan
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[Place of publication not identified] : , : Apress, , [2021] | ||
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Lo trovi qui: Univ. Federico II | ||
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Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes |
Autore | Hughes Ralph <1959-> |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Waltham, MA, : Morgan Kaufmann, 2013 |
Descrizione fisica | 1 online resource (379 p.) |
Disciplina | 005.74/5 |
Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
Record Nr. | UNINA-9910785504103321 |
Hughes Ralph <1959->
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Waltham, MA, : Morgan Kaufmann, 2013 | ||
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Lo trovi qui: Univ. Federico II | ||
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Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes |
Autore | Hughes Ralph <1959-> |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Waltham, MA, : Morgan Kaufmann, 2013 |
Descrizione fisica | 1 online resource (379 p.) |
Disciplina | 005.74/5 |
Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
Record Nr. | UNINA-9910825750903321 |
Hughes Ralph <1959->
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Waltham, MA, : Morgan Kaufmann, 2013 | ||
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Lo trovi qui: Univ. Federico II | ||
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Agile data warehousing project management [[electronic resource] ] : business intelligence systems using Scrum / / Ralph Hughes |
Autore | Hughes Ralph <1959-> |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Amsterdam ; ; Boston, : Elsevier / MK, 2012 |
Descrizione fisica | 1 online resource (379 p.) |
Disciplina | 005.74/5 |
Soggetto topico |
Agile software development
Business intelligence - Data processing Data warehousing Project management |
Soggetto genere / forma | Electronic books. |
ISBN |
1-283-60983-5
9786613922281 0-12-396517-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Front Cover; Agile Data Warehousing Project Management; Copyright Page; Contents; List of Figures; List of Tables; Preface; Answering the skeptics; Intended audience; Parts and chapters of the book; Invitation to join the agile warehousing community; Author's Bio; 1: An Introduction to Iterative Development; 1 What Is Agile Data Warehousing?; A quick peek at an agile method; The "disappointment cycle" of many traditional projects; The waterfall method was, in fact, a mistake; Agile's iterative and incremental delivery alternative; Agile as an answer to waterfall's problems
Increments of small scopeBusiness centric; Colocation; Self-organized teams; Just in time; 80-20 Specifications; Fail fast and fix quickly; Integrated quality assurance; Agile methods provide better results; Agile for data warehousing; Data warehousing entails a "breadth of complexity"; Adapted scrum handles the breadth of data warehousing well; Managing data warehousing's "depth of complexity"; Guide to this book and other materials; Simplified treatment of data architecture for book 1; Companion web site; Where to be cautious with agile data warehousing; Summary 2 Iterative Development in a NutshellStarter concepts; Three nested cycles; The release cycle; Development and daily cycles; Shippable code and the definition of done; Time-boxed development; Caves and commons; Product owners and scrum masters; Product owner; Scrum master; Developers as "generalizing specialists"; Improved role for the project manager; Might a project manager serve as a scrum master?; User stories and backlogs; Estimating user stories in story points; Iteration phase 1: story conferences; Iteration phase 2: task planning Basis of estimate cards to escape repeating hard thinkingTask planning doublechecks story planning; Iteration phase 3: development phase; Self-organization; Daily scrums; Accelerated programming; Test-driven development; Architectural compliance and "tech debt"; Iteration phase 4: user demo; Iteration phase 5: sprint retrospectives; Retrospectives are vital; Close collaboration is essential; Selecting the optimal iteration length; Nonstandard sprints; Sprint 0; Architectural sprints; Implementation sprints; "Spikes"; "Hardening" sprints; Where did scrum come from?; Distant history Scrum emergesSummary; 3 Streamlining Project Management; Highly transparent task boards; Task boards amplify project quality; Task boards naturally integrate team efforts; Scrum masters must monitor the task board; Burndown charts reveal the team aggregate progress; Detecting trouble with burndown charts; Developers are not the burndown chart's victims; Calculating velocity from burndown charts; Common variations on burndown charts; Setting capacity when the team delivers early; Managing tech debt; Managing miditeration scope creep; Diagnosing problems with burndown chart patterns An early hill to climb |
Record Nr. | UNINA-9910462367503321 |
Hughes Ralph <1959->
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Amsterdam ; ; Boston, : Elsevier / MK, 2012 | ||
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Lo trovi qui: Univ. Federico II | ||
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AI Meets BI : Artificial Intelligence and Business Intelligence / / Lakshman Bulusu, Rosendo Abellera |
Autore | Lakshman Bulusu |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Boca Raton : , : Auerbach Publications, , 2020 |
Descrizione fisica | 1 online resource (241 pages) |
Disciplina | 658.472 |
Soggetto topico | Business intelligence - Data processing |
ISBN |
1-00-312208-6
1-000-28195-7 1-003-12208-6 1-000-28193-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Chapter 1 Introduction; Chapter 2 AI and AI-Powered Analytics; Chapter 3 Industry Uses Cases of Enterprise BI--A Business Perspective; Chapter 4 Industry Use Cases of Enterprise BI--The AI-Way of Implementation; Chapter 5 What's Next in AI Meets BI? |
Record Nr. | UNINA-9910860853103321 |
Lakshman Bulusu
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Boca Raton : , : Auerbach Publications, , 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Analytics : the agile way / / Phil Simon |
Autore | Simon Phil |
Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , [2017] |
Descrizione fisica | 1 recurso en línea (303 páginas) : ilustraciones |
Disciplina | 658.4/033 |
Collana |
Wiley & SAS business series
THEi Wiley ebooks |
Soggetto topico |
Business intelligence - Data processing
Decision making |
ISBN |
1-119-42420-8
1-119-42419-4 1-119-42421-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910271007903321 |
Simon Phil
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Hoboken, New Jersey : , : John Wiley & Sons, , [2017] | ||
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Lo trovi qui: Univ. Federico II | ||
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Analytics : the agile way / / Phil Simon |
Autore | Simon Phil |
Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, , [2017] |
Descrizione fisica | 1 recurso en línea (303 páginas) : ilustraciones |
Disciplina | 658.4/033 |
Collana |
Wiley & SAS business series
THEi Wiley ebooks |
Soggetto topico |
Business intelligence - Data processing
Decision making |
ISBN |
1-119-42420-8
1-119-42419-4 1-119-42421-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910818330903321 |
Simon Phil
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Hoboken, New Jersey : , : John Wiley & Sons, , [2017] | ||
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Lo trovi qui: Univ. Federico II | ||
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Big data MBA : driving business strategies with data science / / Bill Schmarzo |
Autore | Schmarzo Bill |
Pubbl/distr/stampa | Indianapolis, Indiana : , : Wiley, , 2016 |
Descrizione fisica | 1 online resource (275 p.) |
Disciplina | 658.4038 |
Soggetto topico |
Business intelligence - Data processing
Big data Business planning - Statistical methods Data mining |
ISBN |
1-119-23884-6
1-119-23888-9 1-119-18138-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Business potential of big data. The big data business mandate -- Big data business model maturity index -- The big data strategy document -- The importance of the user experience -- Data science. Differences between business intelligence and data science -- Data science 101 -- The data lake -- Data science for business stakeholders. Thinking like a data scientist -- "By" analysis technique -- Score development technique -- Monetization exercise -- Metamorphosis exercise -- Building cross-organizational support -- Power of envisioning -- Organizational ramifications -- Stories. |
Record Nr. | UNINA-9910137168103321 |
Schmarzo Bill
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Indianapolis, Indiana : , : Wiley, , 2016 | ||
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Lo trovi qui: Univ. Federico II | ||
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Big data MBA : driving business strategies with data science / / Bill Schmarzo |
Autore | Schmarzo Bill |
Pubbl/distr/stampa | Indianapolis, Indiana : , : Wiley, , 2016 |
Descrizione fisica | 1 online resource (275 p.) |
Disciplina | 658.4038 |
Soggetto topico |
Business intelligence - Data processing
Big data Business planning - Statistical methods Data mining |
ISBN |
1-119-23884-6
1-119-23888-9 1-119-18138-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Business potential of big data. The big data business mandate -- Big data business model maturity index -- The big data strategy document -- The importance of the user experience -- Data science. Differences between business intelligence and data science -- Data science 101 -- The data lake -- Data science for business stakeholders. Thinking like a data scientist -- "By" analysis technique -- Score development technique -- Monetization exercise -- Metamorphosis exercise -- Building cross-organizational support -- Power of envisioning -- Organizational ramifications -- Stories. |
Record Nr. | UNINA-9910812816603321 |
Schmarzo Bill
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Indianapolis, Indiana : , : Wiley, , 2016 | ||
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Lo trovi qui: Univ. Federico II | ||
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Business intelligence : 7th International Conference, CBI 2022, Khouribga, Morocco, May 26-28, 2022, Proceedings / / Mohamed Fakir, Mohamed Baslam, and Rachid El Ayachi |
Autore | Fakir Mohamed |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (301 pages) |
Disciplina | 658.472 |
Collana | Lecture Notes in Business Information Processing |
Soggetto topico |
Business intelligence
Business intelligence - Data processing |
ISBN | 3-031-06458-5 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996475765503316 |
Fakir Mohamed
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Cham, Switzerland : , : Springer, , [2022] | ||
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Lo trovi qui: Univ. di Salerno | ||
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