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Business Analytics questions with correct answers 100%.
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Business Analytics questions with correct answers 100%.
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Business Analytics questions withcorrect answers 100%.
Distinctive Capability ANS - The integrated business processes and capabilities that together serve
customers in ways that are differentiated from competitors and that create an organization's formula
for business success.
What an organization can do better than its competitors
begins with a strategic focus
Strategic Focus ANS - To decide where to focus their resources for the greatest strategic impact,
managers should answer the following questions:
How can we distinguish ourselves in the marketplace?
What key decisions in those processes, and elsewhere, need support from analytic insights?
What information really matters to the business?
What are the information and knowledge leverage points of the firm's performance?
Analytical Competitor ANS - Organizations that use analytics extensively and systematically to outthink
and out-execute the competition
Four Pillars of Analytic Competition ANS - 1. Distinctive Capability
2. Enterprise-wide Analytics
3. Senior Mgmt Commitment
4. Large Scale Ambition
, Five Stages of Analytic Competition ANS - 1. Analytically Impaired - Negligible, flying blind
2. Localized Analytics - Not supporting company's distinctive capabilities
3. Analytical Aspirations - Begins efforts for more integrated data and analytics
4. Analytical Companies - Enterprise-wide perspective, uses analytics for point advantage
5. Analytical Competitors - Enterprise-wide, big results, sustainable advantage
Transformation to Analytic Competitor ANS - 1. Decide current BA capabilities
2. Formulate roadmap
3. Be aware of key issues that enterprises face when adopting analytics
Continuous Experiments ANS - Creates a series of temporary competitive advantages over other
competitors
Fast Cycle ANS - of sensing and responding to external markets and internal business events and
processes -> Competitive Advantage
CRISP-DM definition ANS - Cross-Industry Standard Process
for Data Mining
Data mining methodology that is reliable and repeatable by those with little experience.
CRISP-DM steps ANS - 1. Business understanding
2. Data understanding
3. Data preparation
4. Modeling
5. Evaluation
6. Deployment
BI vs. BA vs. DM - definitions and differences ANS - Business Intelligence - Data sources and warehouses
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