Expert Database Analysis

The Nature and Use of Data

database analysis Data analysis is concerned with the NATURE and USE of data. It involves the identification of the data elements 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.

Database Management Systems

data model The introduction of Database Management Systems (DBMS) like Oracle, SyBase, DB2, Microsoft's SQL Server, MySQL and PostgreSQL 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, implementation independent data analysis.

The initial objective is to define a simple high-level, implementation-independent model which can be used as a basis for further refinement; decisions made at this stage are not irrevocable.

Data Analysis Methods

During data analysis an organization's data is analysed and data structures are built into 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 establishes the nature of data.
Functional Analysis establishes the use of data.

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

Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

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 - A written specification for the database system to be built. Incorporates facts learned during requirement analysis, defines problems and constraints, defines objectives, defines scope and boundaries.
Database Design - A conceptual, logical, and physical design blueprint that specifies the physical implementable database design.
Implementation and Data Loading - Once a DBMS has been installed the new system database itself must be created within the DBMS. Not all databases start completely empty and initial data must be loaded.
Testing and evaluation - The database, once implemented, must be tested. This step in the life cycle offers opportunity to fine-tune the system and SQL for best performance.
Operation (Go Live) - The system is actually in productive usage by the company.
Maintenance and Evolution - As a new system is used flaws are uncovered and the need for additional functionality arise. Requests to fix problems with the system and change requests for enhancements or new requirements create ongoing design needs.