Analytics : the agile way / Phil Simon. 6

By: Simon, Phil, 4 0 16, [, author.] | [, ] |
Contributor(s): 5 6 [] |
Language: Unknown language code Summary language: Unknown language code Original language: Unknown language code Series: ; Wiley & SAS Business SeriesHoboken, New Jersey : John Wiley & Sons, Inc., [2017]46Edition: Description: 1 online resource (xxix, 268 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781119424215ISSN: 2Other title: 6 []Uniform titles: | | Related works: 1 40 6 []Subject(s): -- 2 -- 0 -- -- | -- 2 -- 0 -- 6 -- | 2 0 -- | -- -- 20 -- | | -- -- Data processing. Business intelligence;Decision making. -- -- 20 -- | -- -- -- 20 -- --Genre/Form: Electronic books. -- 2 -- Additional physical formats: AnalyticsDDC classification: | 658.4/033 LOC classification: | HD38.7 | .S535 20172Other classification:
Contents:
Praise for Analytics: The Agile Way; Analytics; Wiley & SAS Business Series; Other Books by Phil Simon; Contents; Preface: The Power of Dynamic Data; Figures and Tables; Introduction: It Didn't Used to Be This Way; A Little History Lesson; Analytics and the Need for Speed; How Fast Is Fast Enough?; Automation: Still the Exception That Proves the Rule; Book Scope, Approach, and Style; Breadth over Depth; Methodology: Guidelines > Rules; Technical Sophistication; Vendor Agnosticism; Intended Audience; Plan of Attack; Next; Notes; Part ONE Background and Trends;Chapter 1: Signs of the Times: Why Data and Analytics Are Dominating Our WorldThe Moneyball Effect; Digitization and the Great Unbundling; Amazon Web Services and Cloud Computing; Not Your Father's Data Storage; How? Hadoop and the Growth of NoSQL; How Much? Kryder's Law; Moore's Law; The Smartphone Revolution; The Democratization of Data; The Primacy of Privacy; The Internet of Things; The Rise of the Data-Savvy Employee; The Burgeoning Importance of Data Analytics; A Watershed Moment; Common Ground; The Data Business Is Alive and Well and Flourishing; Not Just the Big Five;Data-Related ChallengesCompanies Left Behind; The Growth of Analytics Programs; Next; Notes; Chapter 2: The Fundamentals of Contemporary Data: A Primer on What It Is, Why It Matters, and How to Get It; Types of Data; Structured; Semistructured; Unstructured; Metadata; Getting the Data; Generating Data; Buying Data; Data in Motion; Next; Notes; Chapter 3: The Fundamentals of Analytics: Peeling Back the Onion; Defining Analytics; Reporting ` Analytics; Types of Analytics; Descriptive Analytics; Predictive Analytics; Prescriptive Analytics; Streaming Data Revisited; A Final Word on Analytics;NextNotes; Part TWO Agile Methods and Analytics; Chapter 4: A Better Way to Work: The Benefits and Core Values of Agile Development; The Case against Traditional Analytics Projects; Understandable but Pernicious; A Different Mind-Set at Netflix; Proving the Superiority of Agile Methods; The Case for Guidelines over Rules; Scarcity and Trade-Offs on Agile Projects; The Specific Tenets of Agile Analytics; Next; Notes; Chapter 5: Introducing Scrum: Looking at One of Today's Most Popular Agile Methods; A Very Brief History; Scrum Teams; Product Owner; Scrum Master; Team Member; User Stories;Epics: Too BroadToo Narrow/Detailed; Just Right; The Spike: A Special User Story; Backlogs; Sprints and Meetings; Sprint Planning; Daily Stand-Up; Story Time; Demo; Sprint Retrospective; Releases; Estimation Techniques; On Lawns and Relative Estimates; Fibonacci Numbers; T-Shirt Sizes; When Teams Disagree; Other Scrum Artifacts, Tools, and Concepts; Velocities; Burn-Down Charts; Definition of Done and Acceptance Criteria; Kanban Boards; Next; Chapter 6: A Framework for Agile Analytics: A Simple Model for Gathering Insights; Perform Business Discovery; Perform Data Discovery; Prepare the Data
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Circulation Section 		Circulation-Circulating HD38.7 .S56 2017 (Browse shelf) Available C-EB153
Total holds: 0

56

Includes bibliographical references and index.

Praise for Analytics: The Agile Way; Analytics; Wiley & SAS Business Series; Other Books by Phil Simon; Contents; Preface: The Power of Dynamic Data; Figures and Tables; Introduction: It Didn't Used to Be This Way; A Little History Lesson; Analytics and the Need for Speed; How Fast Is Fast Enough?; Automation: Still the Exception That Proves the Rule; Book Scope, Approach, and Style; Breadth over Depth; Methodology: Guidelines > Rules; Technical Sophistication; Vendor Agnosticism; Intended Audience; Plan of Attack; Next; Notes; Part ONE Background and Trends;Chapter 1: Signs of the Times: Why Data and Analytics Are Dominating Our WorldThe Moneyball Effect; Digitization and the Great Unbundling; Amazon Web Services and Cloud Computing; Not Your Father's Data Storage; How? Hadoop and the Growth of NoSQL; How Much? Kryder's Law; Moore's Law; The Smartphone Revolution; The Democratization of Data; The Primacy of Privacy; The Internet of Things; The Rise of the Data-Savvy Employee; The Burgeoning Importance of Data Analytics; A Watershed Moment; Common Ground; The Data Business Is Alive and Well and Flourishing; Not Just the Big Five;Data-Related ChallengesCompanies Left Behind; The Growth of Analytics Programs; Next; Notes; Chapter 2: The Fundamentals of Contemporary Data: A Primer on What It Is, Why It Matters, and How to Get It; Types of Data; Structured; Semistructured; Unstructured; Metadata; Getting the Data; Generating Data; Buying Data; Data in Motion; Next; Notes; Chapter 3: The Fundamentals of Analytics: Peeling Back the Onion; Defining Analytics; Reporting ` Analytics; Types of Analytics; Descriptive Analytics; Predictive Analytics; Prescriptive Analytics; Streaming Data Revisited; A Final Word on Analytics;NextNotes; Part TWO Agile Methods and Analytics; Chapter 4: A Better Way to Work: The Benefits and Core Values of Agile Development; The Case against Traditional Analytics Projects; Understandable but Pernicious; A Different Mind-Set at Netflix; Proving the Superiority of Agile Methods; The Case for Guidelines over Rules; Scarcity and Trade-Offs on Agile Projects; The Specific Tenets of Agile Analytics; Next; Notes; Chapter 5: Introducing Scrum: Looking at One of Today's Most Popular Agile Methods; A Very Brief History; Scrum Teams; Product Owner; Scrum Master; Team Member; User Stories;Epics: Too BroadToo Narrow/Detailed; Just Right; The Spike: A Special User Story; Backlogs; Sprints and Meetings; Sprint Planning; Daily Stand-Up; Story Time; Demo; Sprint Retrospective; Releases; Estimation Techniques; On Lawns and Relative Estimates; Fibonacci Numbers; T-Shirt Sizes; When Teams Disagree; Other Scrum Artifacts, Tools, and Concepts; Velocities; Burn-Down Charts; Definition of Done and Acceptance Criteria; Kanban Boards; Next; Chapter 6: A Framework for Agile Analytics: A Simple Model for Gathering Insights; Perform Business Discovery; Perform Data Discovery; Prepare the Data

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