book

Building Analytics Teams

by John K. Thompson

June 2020

Beginner to intermediate

394 pages

8h 31m

English

Packt Publishing

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Who this book is forWhat this book coversTo get the most out of this bookGet in touch
Becoming data and analytically drivenAn analytical mindsetBuilding an analytics team and an environment for collaborationCollaborators in the analytics journeySelecting successful projectsOrganizational dynamicsCompetitive advantage or simply staying competitiveThe core collaboration/innovation cycleFocusing on self-renewing processes, not projects – an exampleSummary
IntroductionAI in the education systemWe are differentThe original sinThe right homeEthicsSummaryChapter 1 footnotes
Organizational context and considerationInternships and co-op programsDiversity and inclusionNeurodiversityDisciplinary actionLabor market dynamicsA fit to be foundEvolved leadership is a requirement for successContinual learning and data literacy at the organizational levelDefining a high-performing analytical teamThe general data science processTeam architecture/structure optionsThe implications of proprietary versus open source toolsSummaryChapter 2 footnotes
Managerial focus and balanceSponsor and stakeholder managementAn open or fixed mindset?Productivity premiumThe rhythm of workPersonal project portfolioManaging team dynamicsThe front end of the talent pipelineIt takes a teamSimply the bestOrganizational maximsSummaryChapter 3 footnotes
Artificial intelligence and leadershipTraits of successful analytics leadersBuilding a supportive and engaged teamManaging team cohesionBeing the smartest person in the roomGood (and bad) ideas can come from anywhereEmerging leadership roles – Chief Data Officer and Chief Analytics OfficerHiring the Chief Data Officer or Chief Analytics Officer – where to start?SummaryChapter 4 footnotes
You are not the only game in townKnow what to sayKnow how to say itShaping and directing the narrativeKnow before you goHow many of us are out there?There is a proven path to successWhat are you hoping to accomplish?OutsourcingElephants and squirrelsDaily operationsSummaryChapter 5 footnotes
Overcoming roadblocks to analytics adoptionOrganizational cultureData or algorithms – the knee of the curve or the inflection pointA managerial mindsetThe skills gapLinear and non-linear thinkingDo you really need a budget?Not big data but lots of small dataIntroductory projectsValue realizationSummaryChapter 6 footnotes
Analytics self determinationCommunicating the value of analyticsRelative value of analyticsThe value of analytics, made easyEnabling understandingEnterprise-class project selection processUnderstanding and communicating the value of projectsDelegation of decision makingTechnical or organizational factorsGuidance to end usersWhere is the value in a project?Operational considerationsSelling a project – vision, value, or both?Don't make all the decisionsDo the subject matter experts know what "good" looks like?The project mix – small and largeOpportunity and responsibilitySummary
The change management processGetting to know the businessChange managementAnalytics and discoveryAnalytical and production cycles and systems – initial projectsSummary

Stakeholder engagement – your primary purposeBias – accounting for it and minimizing itEthicsSummary
DataAI todayQuantum computing and AIArtificial General IntelligenceToday, we are failingTeaching children to love numbers, patterns, and mathBlending rote memorization with critical thinking as a teaching paradigmSummaryChapter 10 footnotes

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