1. www.monash.edu.au IMS1805 Systems Analysis Topic 4: How do you do it? Guidelines for doing analysis (continued from last week)

2. www.monash.edu.au 2 Agenda Aim: To extend the approach to analysis and model building technique discussed in the last lecture To show how a ‘bottom-up’ approach to process and data modelling helps direct the analytical process

3. www.monash.edu.au 3 2(b) A bottom-up approach to doing data modelling Start with attributes - specific data elements needed in the system Group related attributes and derive entities from these groupings Build relationships between entities from business rules/needs

4. www.monash.edu.au 4 Step 1: Identifying all likely possible entities and attributes Use statements (and inferences) of specific data items Use business documents to identify data elements List all data elements Watch for unstated attributes or composite attributes which need to be broken up Select likely entities (but treat these as provisional, to be reviewed in Step 2)

5. www.monash.edu.au 5 Step 2: Group closely-related data elements to identify entities Note that entities may be physical tangible objects (product, student) or conceptual objects (sale, unit) Make sure every data element from Step 1 is allocated to a relevant entity Make sure every entity makes sense and is complete (are more attributes needed?) Which attribute will be the unique identifier to distinguish between different instances of each entity?

6. www.monash.edu.au 6 Step 3: Establish connections between entities to build E-R diagram Business needs define the need for inter- relationships between entities Database structure flows from E-R diagram: entities define tables, attributes define fields, etc

7. www.monash.edu.au 7 Step 4: Define nature of relationships between entities Degree of relationship: 1-1, 1-many, many- many Name of relationship Cardinality of relationship

8. www.monash.edu.au 8 Step 5: Reality check Prepare sample database tables with sample data to check for reasonableness of model Normalise as required

9. www.monash.edu.au 9 2(c) A bottom-up approach to function decomposition Start with list of low-level processes - specific information actions which are taken Check equivalence of levels, re-assess processes and adjust if necessary

10. www.monash.edu.au 10 Steps 1-4: Identify actions, select processes and convert to logical form Same as for DFD (see last lecture)

11. www.monash.edu.au 11 Step 5: Establishing hierarchy Examine related low-level processes to form groupings - may be based around: Purpose Interaction Shared data elements Place in position on hierarchy chart Derive function names and record on hierarchy chart

12. www.monash.edu.au 12 3. Points to note Note how: The choice of analytical approach drives the diagram (look at all the things from Step 1 which we have excluded from the final model) The requirements of the model drive the analysis which is needed (look at the things which the model made left us uncertain about) Analysis is the process of developing understanding; model-building is an important aspect of analysis Don’t treat models as ends in themselves Implications for your first assignment

13. www.monash.edu.au 13 Process models as drivers of analysis Developing a detailed picture of information processing needs and activities Understanding the interactions between system elements Focussing on specific information needs Determining system scope and partitioning (Note similarities and differences between DFD and FDD in this regard)

14. www.monash.edu.au 14 Data models as drivers of analysis Using data and information needs (entities and attributes) to understand the business Identifying shared data elements and differentiating between specific needs Identifying business rules from data inter- relationships

15. www.monash.edu.au 15 Cross-model analysis Funtion decomposition vs DFD processes Entities and attributes vs data flows and data stores Cross-checking for compatibility between models

16. www.monash.edu.au 16 Summary Bottom-up approaches relate better to your way of seeing the world and to your knowledge of how organisations work As you get more experienced other approaches may become easier Note that the approach drives the nature of the analytical tasks - data gathering, etc. Look at further in a later lecture