Decision-Making and DIKW Model - Week 12
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Questions and Answers

Which skill is primarily categorized as a soft skill necessary for Business Analysts?

  • Database Management
  • Critical Thinking (correct)
  • Data Visualization
  • Technical Writing
  • What ethical challenge is highlighted by the use of big data in organizations?

  • Reduction of operational costs
  • Data proliferation and privacy concerns (correct)
  • Narrowing the scope of available data
  • Increased standardization of operations
  • Which of the following is NOT considered a hard skill for a Business Analyst?

  • Adaptability (correct)
  • Programming
  • Database Management
  • Data Analysis
  • In clustering, what is primarily used to group data?

    <p>Similarities among data points</p> Signup and view all the answers

    Which type of data is considered unstructured and poses new ethical challenges?

    <p>Photographic data from social media</p> Signup and view all the answers

    Which component of a business process primarily involves the transformation of resources and information?

    <p>Activities</p> Signup and view all the answers

    What is the outcome of a well-designed business process regarding cost for a company?

    <p>Reduced costs</p> Signup and view all the answers

    In the data analysis process, which step involves defining goals and organizing resources?

    <p>Planning</p> Signup and view all the answers

    What does the 'data preprocessing' stage primarily involve?

    <p>Cleaning and refining the data</p> Signup and view all the answers

    Which characteristic of well-designed business processes ensures all activities necessary to achieve a business goal are included?

    <p>Complete</p> Signup and view all the answers

    Which type of analytics answers the question 'What is happening?'

    <p>Descriptive Analytics</p> Signup and view all the answers

    How does the use of IT in business processes contribute to increased speed?

    <p>By facilitating quick hand-over of activities</p> Signup and view all the answers

    What role do repositories play in a business process?

    <p>Collecting business records</p> Signup and view all the answers

    Which analytics type is primarily focused on determining what will happen in the future?

    <p>Predictive Analytics</p> Signup and view all the answers

    What is a common tool used in both descriptive and prescriptive analytics?

    <p>Dashboards</p> Signup and view all the answers

    What is the primary goal of prescriptive analytics?

    <p>Determining the best possible decision</p> Signup and view all the answers

    Which enabler would primarily be associated with analysing historical data to answer business-related questions?

    <p>Descriptive Statistics</p> Signup and view all the answers

    Which role does a business analyst play in strategy implementation?

    <p>Evaluating actions to improve business operations</p> Signup and view all the answers

    What is a key benefit of using optimization in prescriptive analytics?

    <p>It identifies the best decision among alternatives.</p> Signup and view all the answers

    In the context of business analysis, what is usually the focus of post-implementation reviews?

    <p>Examining benefits defined in the business case</p> Signup and view all the answers

    Which component is essential for a computer-based information system?

    <p>Computer hardware</p> Signup and view all the answers

    Study Notes

    Week 12

    • The DIKW model shows how data progresses through knowledge.
    • Analytics leads to decisions, which are based on wisdom.
    • Decisions involve considering consequences and stakeholders' responses.
    • Traditional decision-making relies on human judgment, experience, and expertise.
    • Decision types span managerial, tactical, and strategic levels.

    Decision Types

    • Decision-making complexity increases with management level.
    • Operational decisions focus on daily operations, involving data input from transaction processing systems.
    • Managerial/tactical decisions concern resource allocation and short-term strategies.
    • Strategic decisions address long-term organizational issues, needing high-level knowledge.
    • Strategic decisions are usually made in groups.

    Data-driven vs Judgment-driven

    • Manager types demonstrate varying use of analytics and judgment.
    • High data-driven types (Type A) heavily use analytics.
    • High judgment-driven types (Type D) rely heavily on judgment.
    • Intermediate types (Type B and C) use a balanced approach.

    Data Ethics (PAPA Framework)

    • Privacy, accessibility, accuracy, and property are ethical considerations.
    • Privacy concerns personal information, what people can reveal.
    • Accessibility questions who has access and under what conditions?
    • Accuracy deals with data reliability and accountability.

    Extended PAPA Frameworks

    • Newer ethical challenges created by data types (big data, etc), different types of analysis, and social media.
    • These require more considerations in Extended PAPA Frameworks.

    Skills for Business Analysts

    • Soft skills include communication, critical thinking, problem-solving, collaboration, adaptability, negotiation, and time management.
    • Hard skills include data analysis (Excel, SQL, statistical software), data visualizations (Tableau, Power BI), programming (Python or R), technical writing, and database management.

    Week 11 - Clustering

    • Clustering groups data based on similarities.
    • It lacks a target variable.
    • Examples include grouping customers based on demographics and buying behavior.
    • Clusters are often difficult to identify and label.
    • K-means is a referenced clustering algorithm.
    • k values are determined by the analyst.
    • The algorithm assigns data points to the nearest cluster center.
    • It re-computes centers until the cluster assignment stabilizes.

    Association Rule Mining

    • Finds relationships (co-occurrences) amongst data variables.
    • Often used to analyze market basket data.
    • Apriori algorithm frequently identifies subsets that occur together.
    • This is crucial for promoting related products.

    Data Mining vs Statistics

    • Data mining uses a wider range of data than statistics.
    • Statistical analysis typically involves testing hypotheses from smaller samples.
    • Data mining frequently involves analysis of large amounts of data.

    Week 9 - Data Mining

    • Data mining is the process of extracting useful information from large datasets.
    • It uses statistical and algorithmic methods to discover patterns.
    • CRM management, financial analysis, and medical applications are examples.
    • It can provide insights to improve operations.

    Main Types of Data Mining Methods

    • Prediction involves predicting future occurrences.
    • Classification involves sorting data into categories.
    • Clustering involves grouping similar data points.
    • Associations identify co-occurring variables.
    • Time-series analysis examines trends over time.

    Classification vs Regression

    • Classification predicts categorical outputs (e.g., "Yes" or "No").
    • Regression predicts numerical outputs (e.g., temperature).

    Week 6 - Big Data

    • Big data refers to large datasets that traditional methods cannot handle.
    • It has four characteristics: Volume, Variety, Velocity, and Veracity.
    • Big Data can be used in diverse ways, e.g., advertising, healthcare, and retail.
    • Sources of big data include many kinds of digital archives, documents, and media.

    Data Warehouses and Data Marts

    • Data warehouses store an organisation's entire enterprise data.
    • Data marts focus on specific departments or smaller business units.
    • Data warehouses include processed or prepared data.
    • Data marts utilize data from the warehouse but may not process data as deeply.
    • Data lakes are locations that house raw and unprocessed data.

    Week 4 & 5 - Databases

    • Databases store and organize linked records.
    • Tables hold the data.
    • Relationships link different tables based on associated data values.
    • Tables have primary key fields that identify each record uniquely.
    • Foreign key fields in another table link records in different tables.
    • Metadata describes the data.

    Week 4 & 5 - Data Modelling

    • Data modeling involves visually representing database structure.
    • Relational databases organize data in tables.
    • Entity-relationship diagrams (ERDs) show how entities (types of data or things to be represented) relate to one another.

    Week 4 & 5 - ERD Notations

    • Rectangular boxes represent entities (e.g., Customers, Employees, or Sales).
    • Ellipses represent attributes (e.g., customer name or product quantity or price).
    • Diamonds represent relationships.
    • Cardinality represents the relationship’s strength (One to Many, etc).

    Week 3 - Business Process Management (BPM)

    • BPM is a methodical approach to improving or defining business processes.
    • It includes four key stages: Modeling the current process; creating system components to support the updated process; implementing the updated business process; and monitoring its effectiveness (using policies and ongoing assessments)
    • BPM helps streamline workflows, improve efficiency, reduce costs, and ensure improved customer value.

    Week 3 - Varied types of BPM

    • Functional processes may involve a single department or function.
    • Inter-functional processes involve more than one department in a company.
    • Inter-organizational processes require collaboration beyond organizational boundaries.

    BPM Notation

    • BPM notation tools capture processes.
    • Using symbols to indicate different elements of a process helps convey the steps and logic.

    Week 2 - Business Processes

    • Processes are structured networks of activities, encompassing resources, facilities, and data.
    • Information systems are part of business processes.
    • Transforming raw information into a useful output is fundamental to any business process.
    • Increased use of technology has a direct impact on how business processes operate (e.g., increased automation).

    Week 1 - Business Analytics

    • Business Analytics (BA) is a set of procedures and methods for solving business problems through data analysis.
    • Data analysis processes include planning, data pre-processing, modeling, and follow-up.
    • Statistical model results can help provide meaningful, quantitative insights into a business issue.
    • BA uses tools like SQL, Python, R Studio, and Tableau.

    Types of Decision Modeling

    • Deterministic models utilize known data.
    • Probabilistic models incorporate uncertainty using probability distributions.

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    Description

    Explore the intricacies of decision-making processes and the DIKW model in this quiz. Understand how data evolves into knowledge and leads to informed decisions at various managerial levels. Delve into the contrasts between data-driven and judgment-driven decision-making styles.

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