Informix Data Warehouse Processing method

Based on the Informix Data Warehouse system implementation methodology, we can divide the implementation of the data warehouse into the following steps:

1. Business Needs analysis

Business requirements analysis is the basis of data warehouse construction, should be fully communicated with users to understand the user's real needs, avoid the error of understanding, at the same time, should define a good project development scope.

At this stage, the main tasks include:

(1) Set achievable goals and identify all requirements

(2) Determine system architecture

From the perspective of implementation, there are several ways to design a data Warehouse system architecture:

Structuring a Departmental data mart Datamart

Direct construction of enterprise-class data Warehouse Datawarehouse system

Building a Departmental data mart and then developing an enterprise-class data Warehouse system

(3) Determine the data source

Lists the list of data sources that provide data to the Data warehouse. The complexity, scale, and integrity of source data are more important than other factors in building data warehouses. Pay extra attention to which data sources are compatible with the data type, granularity, and content.

(4) Capacity Planning

In addition to architecture, hardware and software resources are critical to the Data warehouse. As part of the requirements definition, it is important to estimate the amount of data that the data Warehouse will store and the processing of the data.

(5) Technical evaluation

When choosing a software and hardware platform, it is a good idea to listen to expert advice, especially for experts who are experienced in a similar environment. Informixdecisionfrontier Data Warehouse Implementation Suite provides users with fast, integrated and complete data warehouse implementation tools.

2. Logical Model Design

The logical model design is mainly refers to the data warehouse data logical expression form. From the point of view of the functional and performance of the final application, the data model of the Data warehouse may be the most important aspect of the whole project. Defining data models for data warehouses and data marts is a complex task that requires the involvement of domain experts.