Data Analytics Value Chain Quiz

Predictive Analytics

• Focuses on what will happen in the future
• Involves disciplines like data mining, algorithm, and machine learning
• Professionals involved are data scientists, statisticians, and statistical modelers
• Key responsibilities include developing statistical models and using statistical techniques

Diagnostic Analytics

• Focuses on why something happened
• No additional information provided

Prescriptive Analytics

• Focuses on what should be done
• Involves disciplines like optimization and simulation
• Professionals involved are functional analysts and RHMFO analysts
• Key responsibilities include utilizing data and leveraging insights

Analytics Manager and Chief Data Officer

• Guide and develop domains like business and industry
• Key responsibilities include making data-driven decisions
• Involve data value chain and decision support system

Analytics Skills and Competencies

• 3 levels: entry, immediate, and expert
• 4 skills: business, organization, technical, and workplace
• 10 competencies including domain knowledge, data management, operational analytics, and more

Analytics Competencies

Domain Knowledge and Application

• Involves understanding the domain, industry, and business
• Key responsibilities include crafting content strategies and formulating case studies

Data Management and Governance

• Involves managing and governing data
• Key responsibilities include enforcing policies and following ethics

Operational Analytics

• Involves deriving insights from analytics
• Key responsibilities include writing business analysis and determining business implications

Data Visualization and Presentation

• Involves crafting compelling visual presentations
• Key responsibilities include creating simple visualizations and determining best visualization techniques

Research Methods

• Involves using scientific and engineering methods to develop new knowledge
• Key responsibilities include understanding and applying the 4-step research method

Data Engineering

• Involves developing analytical applications using ETL and system software
• Key responsibilities include using SQL and NoSQL and creating databases

Statistical Techniques

• Involves applying statistical methods and concepts
• Key responsibilities include determining best statistical approaches and checking data for errors

Data Analysis, Methods, and Algorithms

• Involves employing machine learning and algorithms to develop insights from data
• Key responsibilities include using hypothesis testing and statistical modeling

Data Value Chain

• Refers to the lifecycle of data, allowing for data-driven decisions
• Involves data creation, information, insights, and decision-making
• Disciplines involved include data management, data governance, and data security