Expert Database Analysis

Establishing the nature and use of data

Data analysis is concerned with the NATURE and USE of data. It involves the identification of the data elements which are needed to support the data processing system of the organization, the placing of these elements into logical groups and the definition of the relationships between the resulting groups.

Systems analysts often, in practice, go directly from fact finding to implementation dependent data analysis. Their assumptions about the usage of properties of and relationships between data elements are embodied directly in record and file designs and computer procedure specifications.

The introduction of Database Management Systems (DBMS) has encouraged a higher level of analysis, where the data elements are defined by a logical model or `schema' (conceptual schema). When discussing the schema in the context of a DBMS, the effects of alternative designs on the efficiency or ease of implementation is considered, i.e. the analysis is still somewhat implementation dependent. If we consider the data relationships, usages and properties that are important to the business without regard to their representation in a particular computerised system using particular software, we have what we are concerned with, implementation­independent data analysis.

In data analysis we analyse the data and build a systems representation in the form of a data model (conceptual). A conceptual data model specifies the structure of the data and the processes which use that data.

• Data Analysis = establishing the nature of data.
• Functional Analysis = establishing the use of data.

Data and functional analysis are so intermixed, the we'll use the term data analysis to cover both.

Building a model of an organisation is not easy. The whole organisation is too large as there will be too many things to be modelled. It takes too long and does not achieve anything concrete like an information system, and managers want tangible results fairly quickly. It is therefore the task of the data analyst to model a particular view of the organisation, one which proves reasonable and accurate for most applications and uses. Data has an intrinsic structure of its own, independent of processing, reports formats etc. The data model seeks to make explicit that structure

Database Analysis Life Cycle

When a database designer is approaching the problem of constructing a database system, the logical steps followed is that of the database analysis life cycle:

• Database study - here the designer creates a written specification in words for the database system to be built.
• Database Design - conceptual, logical, and physical design steps take specifications to physical implementable designs.
• Implementation and loading - Once a DBMS has been installed, the database itself must be created within the DBMS. Finally, not all databases start completely empty, and thus must be loaded with the initial data.
• Testing and evaluation - The database, once implemented, must be tested. This step in the life cycle offers the chance to the designer to fine-tune the system for best performance.



• Operation - The system is actually in productive usage by the company.
• Maintenance and evolution - Designers rarely get everything perfect first time, and company requests changes to fix problems with the system or to recommend enhancements or new requirements.