SOLUTIONS

• Solutions List
• Database

1. Database Development
2. Software Development
3. E-Business Solution
4. Microsoft Access Upgrade
5. Data Warehousing

DATABASE DEVELOPMENT

DATA WAREHOUSE SOLUTIONS

Introduction

The need to keep improving management information will always be present. The goal is to provide management and staff with accessibility to concise, accurate and flexible views of all information relevant to their activities. In today's business age, it is not difficult to see how this vision can represent serious business advantage.

Data warehousing is key part of this enigma. It represents the ability to unify, structure and arrange information from a multitude of sources. Then, by using a variety of query and analysis tools, users can obtain data from the data warehouse to assist with operational decision-support.

A Definition

"A Data Warehouse is a copy of data from one or many sources, specifically structured for query, reporting and analysis."

Why a Data Warehouse?

The following summarises a few of the most common reasons to implement a Data Warehouse;

• To isolate the load of query, reporting and analysis activity from the infrastructure supporting operational processing
• To enable use of more appropriate data models and/or database technologies to optimise the performance of query, reporting and analysis
• To simplify query, reporting and analysis across disparate data sources
• To offer secured access to information on a read-only basis thus avoiding the need to grant unnecessary access to operational systems
• To provide a "cleaned" version of the original data so that operational data does not require a similar "cleaning" process
• To provide the ability to extract "as was" reporting relevant to a particular point in time - To provide a facility for the storage of historical data of greater longevity than would normally be kept in operational data sources.

Approach & Methodology

The start point is to identify business areas where more value or leverage is required from operational data and the key sponsors of the project in these areas. Once these broad-based objectives are established, the specific needs of information consumers need to be determined, both in terms of regular defined information and the scope of ad-hoc analysis requirements.

From this knowledge, analysis of the sources can begin in terms of platforms, locations, structure, accessibility and data quality. Once familiarity of the sources is achieved, the design of the warehouse schema and data migration processes can proceed.

Return on Investment (ROI)

The scope of a data-warehousing project may be considerable and encompass many departmental requirements. It is important therefore that certain areas should be prioritised and treated as mini-projects with their own sponsors and their particular objectives. In this way an element of return on investment is seen much earlier.

Techniques

Use of data and process modelling enables a comprehensive business model to be formed. 'Star' and 'Snowflake' Schemas are employed with data transformation tools and techniques to cleanse, de-normalise, and transform data. By combining this with carefully considered indices, the warehouse is optimised for users information access patterns, including ad-hoc queries and highly customised reports.

Products & Tools

The core products and tools employed are Microsoft SQL Server, Data Transformation Services and other specialist tools depending on the requirement.

Make a Further Enquiry

RESOURCES