Informix Data Warehouse Solution

Source: Internet
Author: User
Tags informix

According to the Informix Data Warehouse System implementation methodology, we can divide the data warehouse implementation into the following steps:

1. Business Demand Analysis

Business Requirement analysis is the basis for data warehouse construction. It is necessary to fully communicate with users, understand the real needs of users, avoid misunderstanding, and define the scope of project development.

At this stage, the main tasks include:
(1) set achievable goals and clarify all requirements

(2) determine the system architecture

From the implementation perspective, there are multiple methods to design the data warehouse system architecture:
Construct a department-level data mart DataMart
Directly construct an enterprise-level data warehouse system
First, establish a department-level data mart and then develop an enterprise-level data warehouse system

(3) determine the data source
Lists the data sources that provide data to a data warehouse. The complexity, scale, and integrity of source data have a greater impact on the establishment of a data warehouse than other factors. Pay special attention to which data sources are compatible with the data type, granularity, and content.

(4) Capacity Planning
In addition to the architecture, hardware and software resources are also critical to data warehouses. As part of the requirement definition, it is important to estimate the amount of data to be stored in the data warehouse and process the data.

(5) Technical Evaluation
When selecting software and hardware platforms, it is best to listen to expert suggestions, especially those with experience in similar environments. InformixDecisionFrontier data warehouse implementation kit provides users with fast, integrated, and complete data warehouse implementation tools.

2. Logical Model Design

The logical model design mainly refers to the logical representation of data in the data warehouse. From the perspective of the functions and performance of the final application, the data model of the data warehouse may be the most important aspect of the entire project. Defining a data model for a data warehouse or data mart is a complex task that requires the participation of domain experts.

3. Physical Model Design

During Physical Model Design, the logic model of the Data Warehouse is mainly converted into the physical table structure in the database. ERWin and other auxiliary design tools can be used in physical model design.

Informix adopts the ROLAP mode, and data warehouse data is mainly stored in the InformixIDS (InformixDynamicServer) database. InformixIDS is an industry-leading database engine. It features concurrency, scalability, multi-process/Multi-clue, and is the core of Informix Data Warehouse applications.

4. Data Extraction, cleaning, integration, and loading

Data extraction is a very important step in the establishment of a data warehouse. It extracts, cleans, and integrates data distributed in the user's business system.
(1) define data loading and Maintenance policies
(2) Data Extraction/cleaning/conversion/loading

Informix provides a series of tools to access business system data stored in heterogeneous databases. Informix also provides data replication products. In this way, the system automatically transmits data that meets the rules in a synchronous or asynchronous manner to ensure data integrity and consistency.

InfoMover of Informix allows you to easily define the data extraction, cleaning, integration, and loading processes, and regularly schedule the processes to reduce the complexity of incremental data loading. In addition, Informix Data Loading policies support a wide range of tools from third-party manufacturers, such as Prism, Carleton, and ETI.

5. Manage Data Warehouses

The management of data warehouse metadata is also an extremely important part. Informix MetacubeWarehouseManager provides the GUI. You can manage metadata by dragging the mouse.

6. Data Analysis, Report, query, and other data Performance

User Analysis, reports, and query tools are used to analyze and make decisions. Therefore, all its operations must be very simple, but the functions provided must be very powerful. Informix provides a complete set of tools.

In addition, data mining technology is also an important part of the data warehouse system. Informix provides RedBrickDataMine and third-party manufacturers' products to support data mining applications.

7. Data Warehouse performance optimization and release

The performance of a data warehouse directly affects the system query and analysis response speed. Informix provides tools such as MetaCube to support summary query, sample query, and background query to improve the efficiency of data warehouse query.

In short, Informix provides a fast and complete solution for user data warehouse applications. The Informix Data Warehouse solution enables your data warehouse system to have high performance, high scalability, high openness, and can be customized by yourself. At the same time, Informix also provides professional data warehouse consulting services, this will fully ensure that your data warehouse system is built quickly and timely, and that it can truly play a role.

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