book

Analytics

by Phil Simon

July 2017

Beginner to intermediate

304 pages

5h 54m

English

Wiley

Audiobook available

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A Little History LessonAnalytics and the Need for SpeedBook Scope, Approach, and StyleIntended AudiencePlan of AttackNextNotes
The Moneyball EffectDigitization and the Great UnbundlingAmazon Web Services and Cloud ComputingNot Your Father’s Data StorageMoore’s LawThe Smartphone RevolutionThe Democratization of DataThe Primacy of PrivacyThe Internet of ThingsThe Rise of the Data-Savvy EmployeeThe Burgeoning Importance of Data AnalyticsData-Related ChallengesCompanies Left BehindThe Growth of Analytics ProgramsNextNotes
Types of DataGetting the DataData in MotionNextNotes
Defining AnalyticsTypes of AnalyticsStreaming Data RevisitedA Final Word on AnalyticsNextNotes
The Case against Traditional Analytics ProjectsProving the Superiority of Agile MethodsThe Case for Guidelines over RulesNextNotes
A Very Brief HistoryScrum TeamsUser StoriesBacklogsSprints and MeetingsReleasesEstimation TechniquesOther Scrum Artifacts, Tools, and ConceptsNextNotes
Perform Business DiscoveryPerform Data DiscoveryPrepare the DataModel the DataScore and DeployEvaluate and ImproveNextNotes

The UTC and Project BackgroundProject Goals and KickoffIteration OneIteration TwoIteration ThreeIteration FourResultsLessonsNextNotes
The Value of Business ExperimentsPiLab’s Adventures in AnalyticsA Better Approach to HiringStaffingThe Value of PerksResults and LessonsNextNotes
Project BackgroundBusiness and Data DiscoveryThe Friction BeginsAstonishing ResultsDeveloping OptionsThe Grand FinaleResults and LessonsNextNotes
Paying NursesEnter the ConsultantUser StoriesAgile: The Better WayResultsLessonsNextNotes
Unintended but Familiar ConsequencesEvaluating the ProblemResults and LessonsNextNotes
Life at IACLife at RDCComparing the TwoNextNotes
People IssuesData IssuesThe Limitations of Agile AnalyticsNextNotes
The Genes of MusicThe Tension between Data and DesignNextNotes
A Tale of Two RetailersThe Blurry Futures of Data, Analytics, and Related IssuesFinal Thoughts and Next StepsNotes
BooksArticles and Essays

Content preview from Analytics

Index

A

Ackman, Bill
actionable metrics versus vanity metrics
adoption of technologies
Agile analytics
- business discovery
- compared to predecessors
- data discovery
  - UTC class project
- data modeling
- data preparation
- evaluation
- guidelines
- hiring process and
- improvements
- limitations
- premature action
- score-and-deploy phase
- six-step framework
Agile Analytics (Collier)
Agile methods
- Dynamic Systems Development Method
- estimation techniques
  - Fibonacci numbers
  - relative estimates
  - team disagreement
  - T-shirt sizes
- Extreme Programming
- Feature-Driven Development)
- Nextdoor, app variants
- origins
- releases
- Scrum and
Agile software, Manifesto for Agile Software Development
Agile Software Requirements (Leffingwell)
AI (artificial intelligence)
Airbnb
Alexa (Amazon)
Alphabet/Google, world’s most value companies
Amazon
- Alexa
- AWS (Amazon Web Services)
- Echo
- Fire Phone
- fulfillment prior to order
- Redshift
- selling reviews, Fiverr
- world’s most value companies
“An Essay on the Nature and Significance of Economic Science” (Robbins)
analytics. See also Agile analytics
- Amazon and
- as business projects
- cultures
- data scientists
- defining
  - key performance indicators
- descriptive
- development speed
- versus event-stream processing
- Facebook and
- Google and
- health-care
- Netflix and
- predictive
- prescriptive
- programs, growth
- projects, traditional
- versus reporting
Andreessen, Marc
APIs (application program interfaces)
Apple
- data import and
- iBeacon
- world’s most value companies
Apple Music
Arizona State University, 134.