Business Intelligence Overview
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Questions and Answers

What is the primary objective of the intelligence system described?

  • To entertain the employees with games
  • To eliminate the need for human decision-making
  • To supply suitable information for specific activities (correct)
  • To automate financial transactions

    • What role do data-processing machines play in the intelligence system?

  • They provide manual data entry services
  • They are primarily used for analysis of past data
  • They facilitate auto-extraction and encoding of documents (correct)
  • They encrypt sensitive information only

    • By 2000, what significant change is anticipated in the realm of Business Intelligence?

  • Business Intelligence systems will be obsolete
  • Business Intelligence will be broadly available to various stakeholders (correct)
  • Business Intelligence will become exclusive to IT specialists
  • Information Democracy will be limited to leadership teams

    • How does the intelligence system support organizational functions?

    <p>By managing the acquisition and dissemination of new information</p> Signup and view all the answers

    What is emphasized as essential for thriving in a competitive marketplace?

    <p>Making informed decisions based on accurate and current information</p> Signup and view all the answers

    What does the term 'action points' refer to in the context of the intelligence system?

    <p>Specific areas or roles within the organization that require support</p> Signup and view all the answers

    Which of the following is NOT a function of the intelligence system described?

    <p>Social media management</p> Signup and view all the answers

    What factor is highlighted as a challenge for businesses in the future?

    <p>Staying ahead of the competition through informed decision-making</p> Signup and view all the answers

    What is the primary purpose of Business Intelligence (BI)?

    <p>To support reporting, analysis, and decision making</p> Signup and view all the answers

    Which outcome is NOT associated with implementing Business Intelligence?

    <p>Increased data redundancy</p> Signup and view all the answers

    Which of the following best describes 'single version of the truth' in BI?

    <p>A consensus among stakeholders on data interpretation</p> Signup and view all the answers

    What does BI aim to enhance in terms of decision making?

    <p>Fact-based decision making</p> Signup and view all the answers

    Which entity would most likely benefit from the implementation of Business Intelligence?

    <p>A multinational corporation with extensive data needs</p> Signup and view all the answers

    What is likely a key characteristic of BI systems?

    <p>BI systems enable dynamic reporting and analysis</p> Signup and view all the answers

    Which of the following is a method used for BI training and education?

    <p>Watching informative videos and case studies</p> Signup and view all the answers

    Data Warehousing is commonly discussed alongside which of the following topics in BI?

    <p>Overview of Business Intelligence</p> Signup and view all the answers

    What is a key measure of a successful Business Intelligence (BI) system?

    <p>Widespread usage for better decision making</p> Signup and view all the answers

    Which statement reflects the relationship between BI and business strategy?

    <p>BI must be aligned with the company's business strategy.</p> Signup and view all the answers

    What aspect of BI changes how a company conducts its business?

    <p>Transformation to data-driven decision-making</p> Signup and view all the answers

    What role does the BI Competency Center serve within a business?

    <p>To encourage interaction between users and IT</p> Signup and view all the answers

    Which factor is considered essential for the success of a BI implementation?

    <p>Benefit to the enterprise as a whole</p> Signup and view all the answers

    What is NOT a characteristic of a successful BI system?

    <p>Benefits only specific departments</p> Signup and view all the answers

    How does BI improve business processes?

    <p>By enabling data-driven decision-making</p> Signup and view all the answers

    What is a common misunderstanding regarding BI initiatives?

    <p>They are solely a technical responsibility.</p> Signup and view all the answers

    Which type of measure can be aggregated over all dimensions?

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

    What type of measure typically occurs in snapshot facts?

    <p>Semi-Additive</p> Signup and view all the answers

    Which of the following examples is classified as Non-Additive?

    <p>Average Sales Price</p> Signup and view all the answers

    Which of the following is true about Additive measures?

    <p>They occur in event facts</p> Signup and view all the answers

    In what instance are Non-Additive measures typically encountered?

    <p>In all types of facts</p> Signup and view all the answers

    Which type of measure cannot be aggregated over any dimension?

    <p>Non-Additive</p> Signup and view all the answers

    What does the term 'Semi-Additive' refer to?

    <p>Cannot be aggregated across certain dimensions</p> Signup and view all the answers

    Which of the following statements is true about Different Types of Measures?

    <p>Semi-Additive measures can be summed but not over time</p> Signup and view all the answers

    What is an Independent Data Mart?

    <p>A small data mart designed for a specific business unit without relying on an EDW</p> Signup and view all the answers

    Which of the following best describes the Data Mart strategy?

    <p>A bottom-up approach focusing on individual departments and then integrating later</p> Signup and view all the answers

    Which strategy is typically associated with creating an enterprise-wide data warehouse?

    <p>Enterprise-wide warehouse strategy by Inmon</p> Signup and view all the answers

    What is a key characteristic of operational or transactional systems?

    <p>They focus on day-to-day operations of a business</p> Signup and view all the answers

    What is a primary goal of employing a Data Mart strategy?

    <p>To quickly meet specific business unit needs without waiting for an enterprise solution</p> Signup and view all the answers

    Which of the following departments has the highest funding based on the figures provided?

    <p>Sales with $1,000,000</p> Signup and view all the answers

    What is the significance of correctly executing both data warehousing strategies?

    <p>To achieve a comprehensive enterprise-wide data warehouse</p> Signup and view all the answers

    Which of the following is NOT a characteristic of a Data Mart?

    <p>Integrates data from all parts of an enterprise</p> Signup and view all the answers

    What is a data warehouse primarily designed to support?

    <p>Decision support functions</p> Signup and view all the answers

    Which of the following statements best describes a data warehouse?

    <p>A standardized format of cleansed, integrated data</p> Signup and view all the answers

    In the context of data warehousing, what does 'non-volatile' mean?

    <p>The data does not change frequently</p> Signup and view all the answers

    Which component is essential for data integration in a data warehouse?

    <p>Data cleaning processes</p> Signup and view all the answers

    What role do dimensions play in a dimensional modelling approach?

    <p>They provide context and categorization for facts</p> Signup and view all the answers

    What characteristic distinguishes a dependent data mart from an independent data mart?

    <p>Dependent data marts are directly linked to data warehouses</p> Signup and view all the answers

    What is the primary purpose of metadata in a data warehouse?

    <p>To facilitate data retrieval and management</p> Signup and view all the answers

    Which of the following processes is NOT typically part of ETL in data warehousing?

    <p>Legal compliance auditing</p> Signup and view all the answers

    Which type of data is primarily organized in a data warehouse for analytical purposes?

    <p>Structured data for analytical processing</p> Signup and view all the answers

    What does 'subject-oriented' mean in the context of data warehouses?

    <p>Data is organized around key subjects rather than applications</p> Signup and view all the answers

    What is the significance of data quality processes in a data warehouse?

    <p>To guarantee the accuracy and reliability of data</p> Signup and view all the answers

    Which of the following is NOT a characteristic of a data warehouse?

    <p>Temporary data storage for transactions</p> Signup and view all the answers

    What is typically the first step in the ETL process?

    <p>Data extraction</p> Signup and view all the answers

    What is a key benefit of using a data mart?

    <p>It provides a reduced scope of data for specific analysis</p> Signup and view all the answers

    Study Notes

    Business Intelligence I

    • Course covers Digital Transformation and Data-Driven Organizations
    • Topics include: Digital Transformation, Data-Driven Organizations, Business Intelligence and Data Warehousing, and Analytics
    • Digital transformation is a top priority, but the concept needs a clearer definition
    • Key components of digital transformation include reshaping the operating model ("how") and the customer value proposition ("what")
    • There are four building blocks of digital transformation: Customer Experience, Operational Processes, Business Models, and Digital Capabilities
    • Successful digital transformation does not come from implementing new technologies but transforming the organization to leverage new possibilities
    • Decision-makers need the right information in the right moment, in the right place
    • An information system collects, retrieves, processes, stores, and distributes information to support decision-making and control within an organization
    • Data are streams of raw facts representing events like business transactions
    • Information are clusters of facts that are meaningful and useful to humans, such as decision-making
    • Raw data from a supermarket checkout counter can be processed to produce meaningful information, like the total unit or revenue from sales from a specific store or territory
    • Data-driven organizations need to consider data latency (how long it takes to get the data ready for analysis), analysis latency (delays in analysis of data), and decision latency (delays in taking actions based on decisions).

    Data-Driven Organizations

    • Information systems are collections of interrelated components used to collect, retrieve, process, store, and distribute information
    • Raw data becomes information when processed and organized into meaningful patterns
    • Data becomes useful information when processed correctly
    • The speed and time frame of data analysis is critical for making decisions. The longer it takes, the less value it provides

    Topics

    • Digital Transformation
    • Data-Driven Organizations
    • Business Intelligence and Data Warehousing
    • Business Analytics

    Digital Transformation

    • Slides depicting a comic strip to explore the concept; the strip portrays different viewpoints on the topic.
    • The core elements are shown on a diagram with four sections
    • Reshaping the operating model ("how")
    • Reshaping the customer value proposition ("what")
    • Integrate; Leverage; Create; Enhance; and Redefine the value proposition

    Elements of Digital Transformation

    • Integrate: Incorporating new technologies into existing processes
    • Leverage: Using existing assets to enhance value delivery
    • Create: Developing a new value proposition for customers
    • Enhance: Improving on existing customer value propositions
    • Redefine: Shifting customer value propositions to new strategies

    Digital Transformation Building Blocks

    • Customer Experience
    • Operational Processes
    • Business Models
    • Digital Capabilities

    Data and Information

    • Examples are shown using data from a grocery store checkout
    • Data from transactions can generate insights about specific product and sales territory performance

    Business Intelligence I - T1

    • Topics: Digital Transformation, Data-Driven Organizations, Business Intelligence and Data Warehousing, and Business Analytics

    Business Intelligence

    • BI is a broad category of applications, technologies and processes for gathering, storing, accessing, and analyzing data to aid business users in making better decisions
    • BI architecture has a classic structure
    • Focuses on OLTP (online transaction processing) vs. OLAP (online analytical processing)
    • Data warehousing acts as the central point of data integration
    • Data warehousing strategies help execute decisions (Kimball, Inmon)
    • Modern BI architecture involves cloud and on-premises processes

    Modern BI Architecture

    • Data is streamed in and ingested via techniques such as Apache Kafka or Stream Analytics
    • Batch runs of data are also ingested using ETL processes
    • The data is stored in a data lake
    • The data in the data lake is processed by machine learning using frameworks such as Spark and Databricks
    • Processing results in data warehouses, or potentially in separate lakehouses
    • Analysis and modeling is done against the data in the data warehouse or lakehouse

    Microsoft Fabric

    • A unified platform for data storage, compute, and governance.
    • Includes various components: Data Factory, Synapse Data Engineering, Synapse Data, Science, Synapse Data Warehouse, and more.

    BI in the Cloud

    • Microsoft Azure architecture: Azure Function, Azure IoT Hub, Azure ML Studio, Cosmos DB, Azure SQL, Azure, Data Lake, Preparation & Computation, Data Warehouse, and Presentation.
    • Amazon Web Services (AWS) architecture: Lambda Function, AWS IoT, EMR, Glacier, RedShift, RDS (Relational Database Service), SageMaker, Glue, Kinesis, Streams, Firehose, and Presentation
    • Google Cloud architecture: Cloud IoT, Cloud Function, Cloud Datastore, Cloud SQL, BigQuery, Bigtable, DataProc, Dataflow, PubSub, Data Lab, and Presentation

    Business Intelligence and Analytics

    • Competitive advantage: derived from optimization, predictive modeling, forecasting and statistical analysis
    • Degree of intelligence encompasses alerts, query/drill down, and ad hoc and standard reports

    Business Intelligence Platform

    • High-level architecture: Data Warehouse Environment, Business Analytics Environment, and Performance and Strategy
    • Operational systems include Product Production, Customer Order, Customer Shipment, and Customer Invoice
    • ERP systems
    • Common elements include: Business Rules & Processes, Shared Reference Tables, and Specific Modules connecting different parts of operations

    Data Governance

    • Data governance is much more than just data. It includes the management of data, such as its availability, its usability, its security, and data quality
    • There are 3 important elements for data governance: data availability (what data is available?), how to manage data (who do we contact?), and security (is the data secure or is it compromised?)
    • Data governance has goals, such as empowering data-driven innovation by building and operationalizing Al software, making decisions in context (faster), reducing the cost of data management costs, building data cultures, and migrating the data warehouse to the cloud.
    • Key aspects of data governance are discoverability, security, and accountability

    Data Warehouse Development

    • Typical problem: analyzing daily sales throughout the year in several stores and across different products
    • Key to defining dimensions like Location (Store), Date (Time), Product, and other attributes
    • Dimension tables are used to enhance the level of detail about information.
    • Fact table schema includes measures, such as total sales.

    Dimension Tables

    • Surrounding fact tables. These tables include the attributes or data that describe the fact tables and address how to analyze them
    • Consist of a Dimension Primary Key, Dimension Name, Attributes
    • Often include hierarchies, such as Product—Type—Category or Date—Day—Month—Quarter—Year

    Dimension Models (Variants)

    • Star Schema: simpler and more easily understandable; common and popular
    • Snowflake Schema: more complex but potentially more efficient in cases with a large number of facts

    ETL

    • ETL stands for Extract, Transform, and Load
    • A process to move data from different sources, preparing the data for a data warehouse by cleansing it and transforming it into a usable format, and loading it into the data warehouse
    • Examples include changing format, deduplication, splitting datasets, table operations, and aggregations
    • "Dirty" data issues can arise in different sources. Solutions for cleaning the data include Parsing, Correcting, Standardizing, and Matching the data to consolidate data
    • Loading data involves placing converted data into the database

    Data Governance Frameworks, Tools and Processes

    • Data governance frameworks can help keep data manageable by simplifying the process and identifying crucial elements
    • The concept includes executive sponsorship, data governance, data stewardship, data management, oversight, and operational processes

    Data Governance: Data Quality with DAMA:DMBOK

    • DAMA: Data Management Association (DAMA), which owns the DMBOK (Data Management Body of Knowledge) to describe data quality
    • Six dimensions of data quality: Completeness, Uniqueness, Timeliness, Validity, Accuracy, and Consistency

    Topics

    • What is Data Governance?
    • Data Governance frameworks, tools, and processes
    • Data Governance: Data Quality with DAMA:DMBOK
    • Data Governance: Example Use Cases

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    Description

    Test your understanding of the fundamental concepts of Business Intelligence (BI) and its role within organizations. This quiz covers key elements such as data processing, decision-making enhancements, and future challenges in the BI landscape. Prepare to explore how intelligence systems can drive competitive advantage.

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