Course Brief

Data is used in all organisations to enable people to extract information and make effective decisions. This unit exposes learners to some of the ways data is analysed and used to make effective decisions. Learners will be exposed to different ways of manipulating and presenting data, including spreadsheets. Automating data processing using macros and simple databases will also be explored.

  • This course is offered in 50 contact hours.

Upon successful completion of this unit, learners will be able to:

  1. Describe the importance of data within an organizational context;
  2. Use spreadsheets to generate information from data to support organizational objectives;
  3. Use simple relational databases to address the shortcomings of spreadsheets;
  4. Describe general data accessibility issues;
  5. Describe current industry trends and new developments.

Describe the importance of data within an organizational context:

  • Data as an organizational asset: The importance of data as an organizational asset; the relationship between data and information; the importance of high quality data; characteristics of high quality data (eg validity, reliability, timeliness, fit for purpose, etc.); common problems with organizational data  (eg separation and isolation of data, duplication of data,  data inconsistencies, etc.).
  • Data sources and data collection techniques & tools: Different ways of classifying data (eg primary vs secondary; internal vs external; qualitative vs quantitative); data collection techniques (eg observation, interviews, surveys, simulation, etc.); data collection tools (eg spreadsheets).

 

Use spreadsheets to generate information from data to support organizational objectives:

  • Introduction to Spreadsheets: Different uses of spreadsheets; basic spreadsheet features and navigation; basic data entry and formatting.
  • Apply descriptive statistics to spreadsheet data: Use of basic formulas (eg addition, subtraction, multiplication, division, etc.) and basic functions (eg summations, counts, averages, minimum, maximum, etc.) to manipulate spreadsheet data.
  • Present spreadsheet data using appropriate media: Present data using tabulated description (i.e. tables), graphical description (i.e. graphs and charts), and high-level statistical commentary (i.e. high-level discussion of the results).
  • Interpret spreadsheet data to generate information as a basis for decision-making: Produce basic reports utilizing analysed data to aid in management decision-making.

 

Use simple relational databases to address the shortcomings of spreadsheets:

  • Describe limitations of spreadsheets when data volumes increase: eg cumbersome data retrieval, issues with multi-user access, issues with data integrity and data validation, etc.
  • Describe how spreadsheet limitations can be addressed by relational databases: eg ease of data retrieval, multi-user access, enforcement of data integrity and data validation, etc.
  • Introduction to relational databases: Different uses of relational databases; relational database structure (fields, rows/tuples and tables/relations); primary keys and foreign keys; simple data types.
  • Apply relational database principles and design: Create and populate tables in a database; setup table relationships; perform basic queries; design simple forms; generate simple reports.

 

Describe general data accessibility issues:

  • Describe the related issues of data security (i.e. protecting data against unauthorized users), data integrity (i.e. protecting data against authorized users), and data recovery (i.e. bringing data back to a usable, consistent state after a failure).

 

Describe current industry trends and new developments:

  • Describe recent advances, developments and trends in data analysis/ data management (eg use of software application packages, data warehousing and data mining, etc.).