DTS - Week 3 (Matching)

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Questions and Answers

Match the concepts related to data architecture with their correct descriptions:

Data Architecture = Collection, storage, and processing of data Information Architecture = Converting data into actionable information SSOT = Single Source of Truth MVOTs = Multiple Versions of Truth

Match the characteristics of big data with their definitions:

Volume = Enormous amounts of data generated daily Velocity = Rapid speed of data creation and processing Variety = Diversity of data sources and types Value = Potential insights that drive better decision-making

Match the companies with their big data use cases:

Major U.S. Airline = Improving accuracy of flight arrival times Sears Holdings = Generating personalized promotions Retail Giant = Utilizing customer purchase data for inventory Tech Company = Enhancing web user analytics

Match the following data management strategies with their characteristics:

Centralized data functions = Suitable for data defense with a single CDO Decentralized management = Allows for agility and customization in reporting Data policies and governance = Ensures consistent data application across the organization Decentralized budgets = Focused on offensive investments and tangible ROIs Signup and view all the answers

Match the outcomes with the approaches to data-driven decision making:

5% more productive = Top third companies in data-driven decision-making 6% more profitable = Organizations characterized as data-driven Operational efficiencies = Utilizing big data for flight arrival times Personalized promotions = Reducing time to generate relevant marketing Signup and view all the answers

Match the following roles with their respective focus areas:

Single CDO = Accountable for the entire organization Business unit CDO = Facilitates agility in analytics Centralized budgets = Minimizes risk and reduces costs Decentralized budgets = Closer to business users for effective reporting Signup and view all the answers

Match the following terms with their definitions:

SSOT = Single Source of Truth MVOTs = Multi-View of Truths Data defense = Focus on minimizing risk Data offense = Focus on maximizing ROI from investments Signup and view all the answers

Match the following concepts with the appropriate descriptions:

Feedback loops = Improve data transformation clarity Data architecture = Structured framework for data management Information architecture = Organization of data presentation and access Redundant systems = Result from data silos and duplication Signup and view all the answers

Match the following principles with their significance in data strategy:

Defensive approach = Emphasizes data integrity and compliance Offensive approach = Prioritizes growth and competitive advantage Centralized management = Standardizes data practices across units Decentralized management = Prevents development of data silos Signup and view all the answers

Study Notes

Big Data and Business Analytics

Companies must wisely manage data to remain competitive
Data theft is common, and flawed or duplicate data sets exist within organizations
IT departments are often behind the curve
A coherent strategy balances defensive (security, governance) and offensive (predictive analytics) data management
Data strategy is rarely static; it must dynamically adjust based on competitive pressures and overall corporate strategy
The framework balances "defensive" and "offensive" data uses
Defensive data management minimizes risks (compliance, privacy, fraud)
Offensive data management supports business objectives (revenue, profitability, customer satisfaction)
Data strategy can be influenced by factors like industry regulations (e.g., financial services, healthcare) and competition
Data strategy needs to balance the standardization and flexibility of data

Single Source of Truth (SSOT) vs. Multiple Versions of the Truth (MVOTs)

SSOT: A logical, often virtual, cloud-based repository with one authoritative copy of crucial data (customer, supplier, product)
Requires robust data provenance and governance controls; uses a common language for key data elements
MVOTs: Created from the transformation of SSOT data; specific to business needs
Allows different groups within an organization to transform, label, and report data, creating specific controlled versions of the truth
Crucial for data architecture and flexibility

Data Architecture: SSOT & MVOTs

Implementation of a data architecture that supports both is critical, focusing on data level and useful information transformation
A company's position on the offense-defense spectrum rarely stays static
Good data strategy requires high-quality, granular, standardized data, and controlled creation of multiple versions of the truth

Data Governance, Data Management

Good governance is needed for high-quality, standardized data
Ensuring proper data definitions and consistent rules helps organizations avoid inconsistencies in transformation of data
Feedback loops are important for improvements in data transformations
Data management can be centralized or decentralized, dependent on whether a company's main focus is defense or offense

Single CDO

A single CDO (Chief Data Officer) across the organization is suitable for data defense
Consistent data policies, governance, and standards are important for centralized control
Maintaining uniformity in data practices is crucial for effective strategy execution and data protection

Decentralized Management

Decentralized management is better for offensive strategies
A CDO in each business unit permits agility and customization of data reporting/analytics
Preventing data silos is crucial to reducing redundant systems and duplicated work
Decentralized budgets are more focused on minimizing risk and reducing costs, compared to centralized budgets

Data-Driven Decisions

Data-driven decisions are generally better decisions, relying on evidence rather than intuition
Data analysis enables managers to make decisions based on evidence rather than intuition
Businesses focusing on data-driven decisions perform better financially and operationally

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Description

This quiz explores the critical aspects of managing big data and business analytics in organizations. It covers the balance between defensive and offensive data management strategies and the importance of adapting to competitive pressures. Assess your understanding of these key concepts to enhance your knowledge in this vital field.