Spreadsheets, Data Models, Data Search, & Step-Wise Approach to Modeling

Spreadsheets: Lessons for Makers of Database Management Software

File-based storage approaches have inadequacies as compared to databases. In spite of their drawbacks, spreadsheets, as a file-based approach, are frequently used for data storage in all kinds of organizations.

Makers of database management software should consider lessons that could be learned from the popularity and ubiquity of spreadsheets. Spreadsheets are popular as data storage mechanisms because they have a number of key advantages.

Spreadsheets are popular as data storage mechanisms because of simplicity and ease of use. A spreadsheet application, such as MS Excel, is simple to install and easy to use.

The organization using it for data storage would not need to install special files or packages to make it compatible with existing operating systems or platforms. Spreadsheets are also readily compatible with other applications and can be used in combination with other applications, such as MS Word and MS PowerPoint.

Data from spreadsheets can be directly used with other software products. Problems with spreadsheets are also easy to troubleshoot because of the extensive help files installed on computers and online.

Based on the popularity and ubiquity of spreadsheets, makers of database management software should seriously consider such factors as compatibility, ease of integration, usability and user-friendliness, and simplicity. Makers of database management software should strive to develop products that have such characteristics as spreadsheets.

Data Models and Purpose: Hierarchical, Network, Relational, Entity-Relationship Object-Oriented

What is a data model and what purpose does it serve?

A data model is the scheme that is used to define and determine the relative positions and interrelationships among various data elements, with consideration of the type of data, size of file, etc. This means that a data model serves the purpose of organization. In addition, a data model also serves the purpose of providing a system by which data elements can be processed effectively and efficiently.

Comparison: Hierarchal model, Network, Relational, Entity relationship, Object oriented
  • A hierarchical model involves a rigid structure such that data the lower structural level can only be accessed and used by going through the higher structural levels, which makes this model reliable and sturdy.
  • A network model involves interconnections between different bodies of data, which means that this model is good for a modular approach to data storage.
  • A relational model defines data as mathematical relationships, which allows databases to have clear logical relations that can be use din data processing.
  • An entity relationship model is advantageous because it considers data as entities that have clearly defined relationships that can be used for processing large amounts of data in a short time.
  • An object-oriented model involves the use of objects that allow developers or designers to group and represent data based on specific common characteristics.

Searching Data by Column: Pros and Drawbacks

Charles Babcock, in the 2008 article Database Pioneer Rethinks How Data Is Organized, shows that it is beneficial to search data by column rather than row. One of the pros of searching data by column is that it allows a search to focus on just a single aspect or component of a transaction. It is important to note that data warehouses are recorded per transaction, with each transaction having a variety of elements or components.

For instance, a single transaction in a retail outlet can have such elements as transaction number, amount of sale, date, name of product, etc. If the search were done by row, the search would first retrieve the entire transaction, thereby including all the elements of the transaction. In contrast, searching by column can focus on just one element, such as name of product, for example. This allows users to focus data retrieval and processing on just a single aspect of their transaction or business.

A possible drawback of searching data by column is that it may become time-consuming or resource-intensive to focus on individual transactions, which may require searching by row.

The Step-Wise Approach to Modeling: Strengths & Weaknesses

Michael Chilton, in the 2006 article Data Modeling Using Entity Relationship Diagrams: A Step-Wise Method, discusses the Step-Wise approach to modeling. This approach clearly delineates the different steps involved in developing databases. It should be noted that in other approaches, development may not have clearly defined steps – – steps may overlap and can be interchanged.

In the Step-Wise approach advocated by Chilton, developing databases is perceived as a series or sequence of steps that needs to be followed and completed in order for the database to be properly developed. The strengths of this approach include ease of understanding the database development process, as well as intermediate results after the completion of each step in the process.

A possible weakness of this approach is the lack of flexibility, because the development processes is seen as a rigid sequence of steps.

Reference
  • Babcock, C. (2008, Feb. 25). Database Pioneer Rethinks How Data Is Organized. InformationWeek, 1174, p. 26.
  • Chilton, M. A. (2006, Winter). Data Modeling Using Entity Relationship Diagrams: A Step-Wise Method. Journal of Information Systems Education, 17 (4), pp. 385-394.
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