12.10. Summary

Key Takeaways

  • Big data is voluminous and complex and difficult for systems to process and analyze.
  • Big data is categorized by the three V’s: Volume (size), Variety (# of data types), and Velocity (processing speed).
  • Decision makers should use a systematic process for making decisions.
  • An organization has a wide variety of decisions to make, ranging from highly structured decisions to unstructured decisions.
  • A decision support system (DSS) helps managers make decisions using interactive computer models that describe real-world processes. An  executive information system (EIS) is customized for an individual executive.
  • An expert system gives managers advice similar to what they would get from a human consultant.
  • Business intelligence describes the process that organizations take to collect and analyze data in the hopes of obtaining a competitive advantage. It is an organizational process as well as technology.
  • Data Science is the analysis of large data sets to find new knowledge, and data analytics looks at the past data to try and understand what happened and can also make predictions for the future.
  • Legacy systems often limit data utilization because they were not designed to share data, aren’t compatible with newer technologies, and aren’t aligned with the firm’s current business needs.
  • Most transactional databases aren’t set up to be simultaneously accessed for reporting and analysis. In order to run analytics the data must first be ported to a data warehouse or data mart.
  • There are many different ways to present data findings. Data visualization is the graphical representation of information and data.
  • A data warehouse is a set of databases designed to support decision making in an organization and a data mart is a database focused on addressing the concerns of a specific problem or business unit.
  • Data privacy is huge concern today, especially with the growth in the amount of digital data being created and stored.

Review Questions

  1. What are the benefits and concerns of big data?
  2. What are some typical problems faced by businesses? Can these problems be helped by systems?
  3.  List and describe the phases of the decision making process.
  4. What is the difference between a structured, semi-structured, and unstructured decision?
  5. What is data analytics, and why are many companies using it?
  6. What is the difference between business intelligence, data analytics and data science?
  7. What are some of the tools used to convert data into information?
  8. What is the difference between  canned reports and ad hoc reporting?
  9. How do reports created by OLAP differ from most conventional reports?
  10. List the key areas where businesses are leveraging data mining.
  11. For data mining to work, what two critical data-related conditions must be present?
  12. List the three critical skills a competent business analytics team should possess.
  13. What is the difference between a data mart and data warehouse?


This assignment provides the opportunity to work with the pivot table function in Excel to summarize data for analysis.


  1. Go to the Intro to PivotTables tutorial on GCF LearnFree.org download the practice workbook, and work through the tutorial.
  2. How can the pivot table function be used to support decision-making?
  3. What are some other questions that can be asked of this data?
  4. Create a visualization based on your question for the data.

Share your findings and visualization with the class.


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Information Systems for Business and Beyond Copyright © 2022 by Shauna Roch; James Fowler; Barbara Smith; and David Bourgeois is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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