Business Intelligence and Analytics Overview
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Questions and Answers

What is the primary function of business intelligence?

  • To create marketing strategies.
  • To process transactions in real-time.
  • To manage human resources.
  • To store and analyze data produced by businesses. (correct)
  • Which of the following techniques is NOT typically associated with predictive analytics?

  • Data mining
  • Statistical analysis
  • Credit scoring
  • Cloud computing (correct)
  • Which component is essential for the infrastructure of business intelligence?

  • Customer relationship management software
  • Web-based email systems
  • Social media platforms
  • Data marts (correct)
  • In which area can predictive analytics be particularly beneficial?

    <p>Fraud detection</p> Signup and view all the answers

    Big data analytics often incorporates data from which of the following sources?

    <p>Social media and online customer interactions</p> Signup and view all the answers

    What role do predictive analytics play in decision-support systems?

    <p>They enhance decision-making by forecasting future trends.</p> Signup and view all the answers

    Which of the following is a primary benefit of implementing big data analytics in retail?

    <p>Real-time, personalized shopping experiences.</p> Signup and view all the answers

    What is a key characteristic of the data used in predictive analytics?

    <p>It includes historical data for trend analysis.</p> Signup and view all the answers

    What is one of the main challenges faced when implementing enterprise applications?

    <p>Cost overruns</p> Signup and view all the answers

    Which of the following is a characteristic of next-generation enterprise applications?

    <p>Increased flexibility and web-enabled capabilities</p> Signup and view all the answers

    What does Social CRM primarily incorporate?

    <p>Social networking technologies</p> Signup and view all the answers

    Which of the following is NOT a benefit of incorporating business intelligence with enterprise applications?

    <p>Static data access</p> Signup and view all the answers

    What is a key feature of cloud-based enterprise applications?

    <p>Accessibility from multiple devices</p> Signup and view all the answers

    What is primarily required for effective data standardization, management, and cleansing?

    <p>Standardized data formats</p> Signup and view all the answers

    Why is organizational learning considered a challenge in enterprise application implementation?

    <p>It requires continuous adaptation to technology changes.</p> Signup and view all the answers

    Which of the following best describes a database in the context of enterprise applications?

    <p>An organized collection of data stored centrally</p> Signup and view all the answers

    What is the primary purpose of a data warehouse?

    <p>To consolidate and standardize information for use across the enterprise</p> Signup and view all the answers

    How do data marts differ from data warehouses?

    <p>Data marts are designed for specific business lines or subjects</p> Signup and view all the answers

    What role does Hadoop play in big data processing?

    <p>It enables distributed parallel processing across inexpensive computers</p> Signup and view all the answers

    What is a significant advantage of in-memory computing in big data analysis?

    <p>It can convert hours of processing into seconds</p> Signup and view all the answers

    Which of the following is NOT a key service associated with Hadoop?

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

    What characterizes analytic platforms in the context of big data?

    <p>They are optimized for both relational and non-relational tools to handle large datasets</p> Signup and view all the answers

    Which aspect of data warehouses ensures that the information remains unchanged?

    <p>Data cannot be altered once stored</p> Signup and view all the answers

    What type of users typically benefit from data marts?

    <p>Specific groups focused on particular subjects or business lines</p> Signup and view all the answers

    Study Notes

    Business Intelligence

    • A system for collecting, storing, and analyzing data produced by businesses.
    • Includes databases, data warehouses, and data marts
    • Vendors create and sell the tools needed for BI

    Business Analytics

    • Tools and techniques for analyzing data
    • Includes Online Analytical Processing (OLAP), statistics, models, and data mining
    • These tools are often used to support business intelligence

    Business Intelligence and Analytics for Decision Support

    • Analyze company data to inform future business decisions
    • Can be used by many roles within the organization

    Predictive Analytics

    • Uses data to predict future trends and behaviors
    • Includes statistical analysis, data mining, and data from past experiences
    • The goal is to create assumptions about the future
    • Often used in sales, marketing, finance, fraud detection, and healthcare.
    • Examples include: credit scoring, predicting marketing campaign responses

    Big Data Analytics

    • Analyzing massive datasets collected from sources like social media, online transactions, and customer data.
    • Enables real-time, personalized shopping experiences for online retailers.
    • Can also be used for the analysis of smart cities, using publicly available data, sensor information, and location data from smartphones.

    Business Intelligence Infrastructure

    • Consists of tools used for obtaining data from different business systems and big data sources.

    Data Warehouse

    • Stores a firm's current and historical data from its core operational transaction systems.
    • Consolidates and standardizes information for use by the entire organization.
    • Cannot be altered

    Data Marts

    • A subset of data warehouses
    • Summarized and focused portion of data for specific users
    • Typically focuses on a single subject or line of business

    Hadoop

    • Enables the distributed parallel processing of big data across inexpensive computers
    • Includes several key services:
      • Hadoop Distributed File System (HDFS) to store data
      • MapReduce to break data into clusters for processing
      • Hbase to store data in a NoSQL database
    • Utilized by companies like Yahoo and NextBio

    In-Memory Computing

    • Used for Big Data analysis
    • Stores data in the computer’s main memory (RAM) to avoid delays in retrieving data from disk storage
    • Can reduce processing time from hours or days into seconds
    • Requires optimized hardware

    Analytic Platforms

    • High-speed platforms that use relational and non-relational tools
    • Optimized for large datasets

    Enterprise Application Challenges

    • Enterprise applications can be expensive to purchase and implement
    • Many projects experience cost overruns and long development times
    • Technologies, business processes, and organizational learning can all change, adding complexity
    • Switching costs and dependence on software vendors present challenges
    • Data standardization, management, and cleansing are critical for accurate analysis

    Next-Generation Enterprise Applications

    • Enterprise solutions/suites
      • Makes applications more flexible, web-enabled, and integrated with other systems.
      • Includes cloud-based versions and versions for mobile platforms
      • Also available for small and medium-sized businesses

    Next-Generation Enterprise Applications Continued

    • Social CRM
      • Incorporates social networking technologies
      • Company social networks track social media activity
      • Used for social media analytics and campaigns
    • Business intelligence
      • Integrated with other enterprise applications
      • Enables flexible reporting, ad hoc analysis, "what-if" scenarios, digital dashboards, data visualization, and AI machine learning

    Databases

    • An organized collection of data stored centrally for various informational system applications

    Why Collect Data?

    • To enable and improve business operations
    • To support decision making
    • To increase efficiency
    • To gain competitive advantages

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    Description

    This quiz covers the fundamentals of Business Intelligence and Analytics, including key concepts, tools, and techniques used to analyze data for decision-making in organizations. Learn about the role of predictive analytics, big data, and how these processes support strategic business goals.

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