Interview Users of Data

Interviewing users of data is a crucial step in the process of establishing business rules, as it allows organizations to gather valuable insights and perspectives from the individuals who interact with the data on a daily basis. The primary purpose of conducting user interviews is to ensure that the business rules accurately reflect the organization's operational requirements, while also addressing the needs and expectations of the end users. In this context, user interviews serve several important functions:

1. Identifying User Requirements: By interviewing users of data, organizations can gain a thorough understanding of the specific needs and expectations of different stakeholders. This information helps in designing business rules that effectively address user requirements, such as data access, data validation, and process automation, leading to improved data quality and overall user satisfaction.
2. Uncovering Implicit Knowledge: Users often possess valuable, tacit knowledge about the data and its underlying business processes, which may not be documented or explicitly communicated. Interviewing users allows organizations to tap into this implicit knowledge and incorporate it into the business rules, ensuring that the rules accurately represent the real-world context and nuances of the data.
3. Detecting Data Anomalies and Inconsistencies: Users who interact with the data regularly may be aware of existing anomalies, inconsistencies, or errors within the data. Interviewing these users can help organizations identify potential data quality issues and develop business rules that address these problems, thereby improving the overall accuracy and reliability of the data.
4. Ensuring User Acceptance: Involving users in the process of establishing business rules fosters a sense of ownership and buy-in among the user community. By incorporating user feedback and addressing their concerns, organizations can ensure that the business rules are readily accepted and adopted by the users, ultimately leading to more effective implementation and enforcement of the rules.
5. Facilitating Change Management: The introduction of new business rules may entail significant changes to existing processes and workflows. Interviewing users can help organizations anticipate potential challenges and resistance to change, allowing for the development of targeted change management strategies that minimize disruption and ensure a smooth transition to the new business rules.

After you have completed your analysis of the existing business objects and rules, the next logical step in the process of Requirements Analysis is to interview those within the organization who use the data in the database. Their collective insights into how data is used help in revising (for example, adding to or subtracting from) the list of business objects and rules collected earlier. Users of data include an organization’s employees and managers. There are three major reasons why users of data are interviewed by database designers:

1. To determine how data are currently being used and perceived
2. To determine whether users require additional information
3. To determine future growth requirements

• Current usage of Data:
  How an organization currently uses its data is determined not only by examining the existing database(s), but also by interviewing those who use the data. Stories on CD, Inc., for example, has a data-entry form to process customer orders and a listing of its distributors in a Rolodex. Current informational needs of the company prescribe that distributors be considered a business object. Interviewing the current users of data: 1) Ted and 2) Lisa Martin in this case has uncovered this “out of sight” paper-based data sources.

Rarely will an analysis of an organization’s existing database (whether legacy or paper-based) reveal the full range of an organization’s informational needs. If that were the case, the role of the database designer in creating a database would be greatly diminished. Consider again the case of Stories on CD, Inc. Nowhere in their legacy database (supplemented with paper-based data entries) is there information to indicate that brochures are sent out three times per year to advertise their product. However, Lisa revealed during an interview that she uses word-processing software to prepare descriptions of the CDs each time brochures are sent out. Knowing this, the designer can include a field in the CDs table to enter CD descriptions. Lisa will now be able to query the database to extract that information for the brochures. This will be a great time-saver for the business.

• Future needs:
  Interviewing data users about future needs enables the designer to rethink design options. For example, if the interview of Ted and Lisa revealed that they intended to sell CDs outside of the U.S. in about 18 months, the designer might refrain from placing any field constraints on address-related fields that would preclude data entry about overseas customers. Again, documentation of the interviews is extremely important. As questions arise while designing the logical schema, notes taken here are reviewed and can point the designer in the right direction if more user information is needed.
  Interviewing users of data is an indispensable component of the process of establishing business rules. By engaging with users and incorporating their insights, organizations can develop business rules that accurately reflect the needs of the end users, improve data quality, and facilitate user acceptance and adoption. This, in turn, contributes to the overall effectiveness and success of the organization's data management initiatives.

In the context of databases, the terms data, information, and knowledge represent different levels of abstraction and understanding:

1. Data:
   • Definition: Data refers to raw, unprocessed facts and figures without any context or meaning on their own. In databases, data is stored as individual entries or records in tables.
   • Example: Consider a database storing customer transactions. Data could be the numbers and strings representing individual transactions, such as `Customer_ID: 12345`, `Transaction_Amount: 50.75`, `Transaction_Date: 2024-08-27`.
   • Role in Databases: In databases, data is the foundation. It is the atomic level of information that is collected and stored in tables. It is usually organized into rows (records) and columns (fields) within a database.
2. Information:
   • Definition: Information is data that has been processed, organized, or structured in a way that adds context, making it meaningful. Information is the next step up from data and answers questions like "who," "what," "where," and "when."
   • Example: Taking the raw data mentioned above, information could be a report that shows the total amount spent by a particular customer on a specific date, such as "Customer 12345 spent $50.75 on 2024-08-27."
   • Role in Databases: In databases, information is often generated through queries, reports, or views. The database management system (DBMS) processes raw data to produce meaningful information for end-users or applications.
3. Knowledge:
   • Definition: Knowledge is derived from information by analyzing, interpreting, and applying it to make decisions or predictions. It is the understanding or insight gained from combining information with experience, context, and understanding of the underlying patterns.
   • Example: Knowledge in the context of our example might involve understanding customer behavior trends, such as "Customers who spend over $50 in a single transaction are likely to make another purchase within a week." This kind of insight can be used to drive marketing strategies or decision-making.
   • Role in Databases: While databases store data and help generate information, knowledge often requires further analysis, such as through data mining, machine learning, or business intelligence tools. Knowledge is used to make informed decisions and to derive strategies based on the information provided by the database.

Summary

• Data is the raw, unorganized facts stored in a database.
• Information is processed data that has meaning and context.
• Knowledge is the insight or understanding derived from information, often used to guide decisions.

These distinctions help in understanding how databases are used to not only store data but also to produce actionable insights that can drive decision-making.
The next lesson examines the next step in the Requirements Analysis process: creating a data flow diagram.