MIS test 3

Durability

. Durability: Durability ensures that once a transaction is committed, the changes made by the transaction persist, even in the event of system failures. The changes become permanent and are not lost, providing reliability to the system. Example: After a successful fund transfer in a banking system, the system guarantees that even if the server crashes immediately after the transaction, when the system comes back online, the completed transaction will still be reflected in the database. Durability ensures the permanent storage of the committed transaction's changes.

1) Compare and contrast between the four different types of decisions: structured

.Characteristics: Well-defined, routine, and repetitive. Usually based on clear procedures or rules. Data-driven and easily automated. b. Level of Decision-making: Mostly operational or lower-level managerial decisions. c. Employees Making These Decisions: Often made by lower-level employees or automated systems. d. Decision Length: Typically short-term, applied within a short time frame. e. Frequency: Frequently made, sometimes daily or multiple times a day.

1) Explain with examples the 4 ACID properties of TPS - Atomicity, Consistency, Isolation, and Durability

1. Atomicity: Atomicity refers to the "all-or-nothing" characteristic of a transaction. It ensures that either all operations within a transaction are completed successfully, or if any part fails, the entire transaction is aborted, and the system remains unchanged. Example: Consider a bank transfer where money is withdrawn from one account and deposited into another. Atomicity ensures that if the withdrawal succeeds but the deposit fails (due to an error), the entire transaction is rolled back, and the money is returned to the original account, maintaining consistency.

1) Explain the characteristics of Executive Information Systems that fulfill these characteristics/needs of senior executive level decision making. a. Explain what Digital Dashboards are, and what they look like, or how they are used.

1. Strategic Information: Strategic Data: EIS provides high-level, summarized, and strategic information rather than detailed operational data. It offers insights into the organization's key performance indicators (KPIs), trends, and critical metrics aligned with strategic goals. 2. User-Friendly Interface: Intuitive Design: EIS platforms feature user-friendly interfaces with easy-to-understand visualizations, making it convenient for senior executives to interpret complex data quickly. 3. Customization and Flexibility: Tailored Views: EIS allows customization of dashboards, enabling executives to focus on specific metrics or areas of interest. This flexibility ensures that executives can access the information most relevant to their decision-making. 4. Real-time Data: Timely Updates: EIS often provides real-time or near-real-time data updates, ensuring that executives have access to the most current information when making critical decisions.

Explain the unique/unusual characteristics/needs of senior executive level decision making

1. Strategic Perspective: Long-term Impact: Senior executives focus on decisions that have far-reaching consequences, affecting the organization's long-term direction, growth, and sustainability. 2. Complexity and Uncertainty: Ambiguity: Decisions at this level often involve navigating through ambiguous or uncertain situations where there might not be clear-cut solutions or historical data to rely on. 3. Risk and Responsibility: High Stakes: Decisions made by senior executives can have a profound impact on the organization's success or failure, involving substantial risks and responsibilities. 4. Information Processing: Need for Comprehensive Data: They require access to comprehensive and timely information from various sources to make informed decisions, often relying on data-driven insights and analytics. 5. Stakeholder Management: Balancing Multiple Stakeholders: Executives need to consider the interests of various stakeholders - shareholders, employees, customers, communities, etc. - and balance competing priorities.

Consistency

2. Consistency: Consistency ensures that a transaction moves the database from one consistent state to another. In other words, the data remains valid and meets all integrity constraints after the transaction completes. Example: In an online ticket booking system, if a user purchases multiple tickets, the system ensures that after the transaction is completed, the total number of available tickets decreases by the number of tickets purchased. This maintains the consistency of available ticket counts.

Isolation

3. Isolation: Isolation ensures that concurrent transactions do not interfere with each other. It allows transactions to execute independently of and without being affected by other concurrently executing transactions. Example: In a banking system, if two customers simultaneously transfer money between their accounts, the system ensures that each transaction is processed independently and without interference. Isolation prevents one transaction from accessing the data being modified by another transaction until it is completed.

Compare and contrast between Atomicity, Consistency, Isolation, and Durability

Comparison: Common Objective: All ACID properties aim to maintain data integrity, reliability, and consistency within a transactional environment. Interaction: While each property addresses different aspects of transaction processing, they are interrelated and work together to ensure the overall reliability of transactions. Contrast: Focus: Atomicity deals with the success or failure of an entire transaction, while consistency ensures the database remains valid. Isolation addresses concurrent transaction execution, and durability ensures the persistence of committed changes despite system failures. Timing: Atomicity and Durability primarily focus on the transaction's execution and completion, while Consistency and Isolation are concerned with the transaction's interaction with other transactions and the database state. In summary, while each property serves a distinct purpose in maintaining transactional reliability and data integrity, they collectively contribute to ensuring the integrity of the database and the reliability of transaction processing within a system.

1) Three types of Analyses that you can do with Executive Information Systems. Know that these are different than the three types of analyses that you can do with DSS. For the three EIS-specific analyses, too, know what the analyses are, what you can learn from each of them/what kinds of questions you can answer using each of them; compare and contrast between them; be able to provide your own examples of each or be able to identify a given example with the type of analysis it represents (along with suitable explanation) a. Consolidation Analysis b. Drill-Down Analysis c. Slice-and-Dice Analysis (also known as Online Analytical Processing (OLAP))

Consolidation Analysis: Purpose: Consolidation analysis involves aggregating data from various sources or departments to create a unified view of the organization's overall performance or a specific aspect. What You Can Learn: Organizational Performance: Understand how different divisions, departments, or regions contribute to the overall performance. Identify Trends: Analyze trends across different segments of the organization to identify areas of strength or weakness. Example: In a multinational company, using consolidation analysis, executives can compare sales performance across different global regions to identify which regions are driving overall revenue growth.

decision support systems (DSS)

DSS assist in complex decision-making by analyzing data and providing insights or models to support managerial decisions. They provide interactive tools and models that allow users to explore different scenarios and assess the potential outcomes of decisions. Example: A financial institution might use a DSS to evaluate different investment portfolios. It can analyze market trends, risk factors, and potential returns, allowing financial advisors to make informed investment recommendations.

Know the similarities and differences between TPS, MIS, and DSS differences.

Differences: Purpose: TPS primarily focuses on recording and processing routine transactions. MIS is geared towards providing summarized reports and information for managerial control and decision-making. DSS is designed to support decision-making in more complex and unstructured situations. Level of Analysis: TPS deals with operational-level data processing, focusing on day-to-day transactions. MIS operates at a managerial level, summarizing and presenting information for mid-level decision-makers. DSS operates at a higher analytical level, offering tools for exploring data and supporting strategic decisions. Scope of Use: TPS is primarily used for transactional data processing and ensuring operational efficiency. MIS is used for managerial control, monitoring, and planning. DSS is used for analyzing data to support decision-making in situations with greater complexity and uncertainty. Users and Decision Types: TPS users are primarily operational staff involved in transactional activities. MIS users are managers and department heads who need summarized information for planning and controlling. DSS users are typically higher-level managers or decision-makers dealing with strategic decisions.

Drill-Down Analysis:

Drill-Down Analysis: Purpose: Drill-down analysis involves examining detailed data by progressively breaking it down into more granular levels or specific components. What You Can Learn: Detailed Insights: Obtain detailed information by drilling down from summarized data to specific transactions or components. Identify Root Causes: Investigate the underlying factors contributing to trends or issues observed at higher levels. Example: Starting with an overview of company-wide sales figures, executives can drill down to specific product categories, then further to individual product sales to identify top-performing or underperforming products.

executive information systems (EIS)

EIS are tailored for top-level executives to provide them with summarized information from various sources to support strategic decision-making. They typically offer easy-to-read dashboards or summaries of critical performance indicators. Example: An EIS for a CEO might display key performance metrics like overall revenue, market share, and profitability trends across different regions or product lines. It helps executives get a quick overview of the organization's health.

1) Explain what are Enterprise Resource Planning (ERP) systems. How do they relate to TPS?

Enterprise Resource Planning (ERP) systems are integrated software solutions that facilitate the management of an organization's core business processes and resources. They allow for the centralization and automation of various functions, such as finance, human resources, supply chain, manufacturing, and customer relationship management, among others. Key features of ERP systems include: Integration: ERP systems consolidate data and processes across various departments and functions within an organization into a single unified system. Automation: They automate routine tasks and workflows, streamlining operations and reducing manual efforts. Data Analytics: ERP systems provide tools for data analysis and reporting, enabling informed decision-making. Standardization: They often come with standardized processes that help organizations adhere to best practices and industry standards. Relationship between ERP and TPS: TPS as a Component: Transaction Processing Systems (TPS) serve as the backbone or operational foundation within an ERP system. TPS within an ERP handle day-to-day transactions, recording, and processing data related to routine business activities such as sales, purchases, inventory, and payroll. Integration: ERP systems incorporate TPS modules to manage and process transactional data seamlessly across various departments. For instance, TPS functionalities in sales, inventory, or finance modules are integrated into the larger ERP structure.

a. Factors (also known as Independent Variables)

Factors (Independent Variables): Purpose: Factors are variables that potentially influence or predict the outcome of interest. They are inputs or independent variables used in the decision model to analyze their impact on the dependent variable.

1) Why are ERP systems an example of systems thinking in action?

Holistic View and Feedback Loops: Comprehensive Data Flow: ERP systems provide a comprehensive view of an organization's operations by collecting and analyzing data from multiple sources. This comprehensive view enables decision-makers to understand how changes in one area affect the entire organization. Feedback Mechanisms: ERP systems often incorporate feedback mechanisms that allow for continuous improvement. They capture data on processes, performance, and outcomes, providing insights for optimizing operations and fostering continuous learning. Focus on Relationships and Wholeness: Emphasis on Relationships: Systems thinking involves understanding relationships between components within a system. ERP systems emphasize the relationships between different departments, functions, and processes, recognizing their interconnectedness and impact on the overall organization. Addressing Wholeness: ERP systems aim to manage an organization as a whole rather than as isolated departments or functions. They facilitate a more cohesive approach to managing resources and operations, aligning with the systems thinking principle of addressing the system's entirety.

managerial information systems (MIS),

MIS provide managers with reports and tools to facilitate decision-making and operational activities. They aggregate data from various sources within the organization and present it in a format that helps managers make informed decisions. Example: An MIS in a manufacturing company might generate regular reports on production levels, inventory status, and sales figures. Managers use this information to analyze performance and plan production schedules.

Link between Factors, Outcome of Interest, and Coefficients:

Positive Linear Relationship: A positive coefficient indicates that an increase in the factor leads to an increase in the outcome of interest. Negative Linear Relationship: A negative coefficient suggests that an increase in the factor results in a decrease in the outcome of interest. Nonlinear Relationship: The relationship between factors and the outcome isn't linear. It can be curved or exhibit varying patterns, and the coefficients reflect this complex relationship.

a. Coefficients

Purpose: Coefficients represent the weights or values assigned to factors in the decision model. They indicate the strength and direction of the relationship between factors and the outcome of interest.

a. Decision/Outcome of Interest (also known as Dependent Variable)

Purpose: The outcome of interest represents the variable that the decision model aims to predict or explain. It is influenced by the factors or independent variables.

Know the similarities and differences between TPS, MIS, and DSS

Similarities: Data Handling: All three systems deal with data in some capacity. TPS collects and processes operational data, MIS aggregates and summarizes this data for managerial use, and DSS further analyzes this information to support decision-making. Information Processing: They all involve processing information but at different levels of complexity and for different purposes. TPS focuses on transactional data processing, MIS organizes data for managerial insights, and DSS analyzes data for decision-making. Supporting Decision-Making: Each system contributes to decision-making in its own way. TPS provides the foundational data, MIS offers summarized information for managers to make operational decisions, and DSS provides analytical tools to aid in complex decision-making.

Slice-and-Dice Analysis (OLAP):

Slice-and-Dice Analysis (OLAP): Purpose: Slice-and-dice analysis, also known as Online Analytical Processing (OLAP), involves multidimensional analysis by manipulating data from different viewpoints or dimensions. What You Can Learn: Comparative Analysis: Compare data across multiple dimensions (e.g., time, geography, product lines) to identify patterns or relationships. Trend Analysis: Analyze data from different perspectives to uncover trends and correlations not immediately apparent in traditional views. Example: Using OLAP, executives can analyze sales data by both product category and geographical region simultaneously to identify which product categories perform best in specific regions. Comparison: Focus: Consolidation analysis focuses on aggregating data for an overall view, while drill-down delves deeper into specifics. Slice-and-dice (OLAP) allows for multidimensional analysis across various perspectives. Granularity: Drill-down offers progressively more detailed data, while slice-and-dice allows for exploring data from multiple dimensions simultaneously. Purpose: Consolidation and drill-down often complement each other, with consolidation providing an overview and drill-down offering detailed insights. Slice-and-dice (OLAP) focuses on multidimensional analysis for pattern recognition and comparative analysis.

Explain with examples what are summary reports and exception reports

Summary Reports: Definition: Summary reports condense and aggregate data to provide an overview or summary of information. They present key metrics, totals, averages, or other aggregated data points to give a high-level view of a particular aspect of the business.Example: Sales Summary Report: This report might display total sales revenue for a specific period, broken down by regions, products, or sales representatives. It summarizes the sales performance, providing an overview of which regions or products are performing best. Exception Reports: Definition: Exception reports highlight deviations, anomalies, or instances that fall outside predefined thresholds or norms. They focus on presenting data that doesn't conform to expected or standard patterns, requiring attention or further investigation. Example: Inventory Exception Report: This report might list products with unusually low or high inventory levels. Items with stock levels below a set threshold might indicate a need for restocking, while those with excessive inventory might signal potential issues with demand forecasting or stocking procedures.

1) Explain with examples what transaction processing systems (TPS)

TPS are responsible for processing routine transactions efficiently and accurately. They handle the day-to-day operations of an organization, recording and processing data resulting from business transactions. Example: Consider a retail store's TPS that records sales transactions, manages inventory, and processes payments at the point of sale. It captures every sale made, updates inventory levels, and records financial transactions.

Differences between Factors and Coefficients:

Variables vs. Constants: Factors are variables, while coefficients are constants in the context of a specific model. Roles: Factors represent the input variables that can vary, whereas coefficients are fixed values that determine the strength and direction of the relationship between factors and the outcome in the model.

highly unstructured

a. Characteristics: Extremely ambiguous, complex, and novel situations. Often no precedence or available information to rely upon. Require significant creativity and out-of-the-box thinking. b. Level of Decision-making: Typically reserved for unprecedented situations at the highest levels of management. c. Employees Making These Decisions: Generally made by top-level executives or organizational leaders. d. Decision Length: Highly variable, might have both short and long-term implications. e. Frequency: Extremely rare, occurring only in exceptional and unique circumstances.

unstructured

a. Characteristics: Lack specific procedures or rules to follow. Often involve high levels of uncertainty or ambiguity. Highly reliant on human judgment, creativity, and intuition. b. Level of Decision-making: Strategic or higher-level managerial decisions. c. Employees Making These Decisions: Usually made by senior management or top-level executives. d. Decision Length: Generally long-term, impacting the organization over an extended period. e. Frequency: Infrequent, occurring occasionally due to their complexity and strategic nature.

semi-structured

a. Characteristics: Partially defined, some aspects follow procedures, while others require judgment. Often involve some amount of human judgment or interpretation. Data might not be as readily available or might need some processing. b. Level of Decision-making: Middle management or departmental level decisions. c. Employees Making These Decisions: Usually made by mid-level managers or experts in the relevant field. d. Decision Length: Can vary, from short to medium-term, depending on the complexity. e. Frequency: Occur on a regular basis but might not be as frequent as structured decisions.

Purpose of Components:

d. Purpose of Components: Outcome of Interest: It's the variable being predicted or explained by the model. Factors: These are the variables that potentially influence the outcome and are the inputs into the model. Coefficients: They indicate the extent and direction of the impact of factors on the outcome, acting as the 'multipliers' or 'weights' for each factor.