While traditional Data Warehousing methods can be expensive, time consuming and involve unacceptably high risks, there are now technologies and methodologies available that can minimise those risks and support more agile and informative approaches.
Focus consultants have deep expertise in these tools and methods, and an unrivalled reputation in this new data warehousing paradigm.
Focus also recognises that the technical objectives for a data warehouse can be many and varied. For example:
- To separate database intensive tasks associated with querying and reporting from the databases that support transaction processing systems
- To use data models and/or server technologies that speed up querying and reporting (differing from those optimised for transaction processing)
- To simplify the data structures and make them more meaningful and easy to use for information consumers
- To combine data from multiple data sources - current or historical, internal or external - into a coherent form which is easy to use for information consumers
- To improve the quality and consistency of data available to for information consumers - "one version of the truth"
- To provide a repository of historical data for a longer span of time than is held in a transaction processing system
- To enhance data security by separating the data used by information consumers from the information maintained in transaction processing systems
- Often, many or all of the above are objectives
- There may be immediate priorities, but also longer term objectives to build an enterprise capability stepwise
As a result, the specific technologies, data architecture and governance framework that are essential to a successful data warehousing solution will also vary.
Focus assist clients with a different stages of maturity, as they pursue a robust data warehousing solution that meets the essential technical and business objectives. We assist with:
- establishing business priorities for information assets
- design an appropriate data architecture
- chosing the right technologies
- analysing detailed business information requirements
- establishing a reliable set of metadata - the foundation of sustainable data warehouse
- data profiling and data quality assessments
- developing appropriate data models
- automating data transfer, data cleansing and data transformations
- establishing an information governance framework
The business objectives for a data warehouse solution often coincide with the business objectives of a business intelligence, reporting, scorecarding, dashboard, planning or performance management solution. In such cases, our breadth of expertise can ensure that key information interfaces and other relevant details are managed effectively.
Metadata Driven Design
Metadata is the information that describes, categorises and classifies enterprise data. The collection and management of metadata is the key to effective data governance.
Focus also advocates the use of Metadata Driven Design to ensure the success of your enterprise information management projects.
The use of advanced data discovery & data profiling tools enables the capture of metadata from all source systems to be used in the design and delivery Information Management projects. The use of metadata in the design process provides consistency, speed and flexibility.
- Consistency – Through the creation of common definitions for enterprise terms and business rules a set of standards for the handling of all data can be defined. These standards are then enforced though the use of Metadata to provide a consistent and accurate output for all data.
- Speed - The collection and use of Metadata in the design process means a set or reusable Information assets are created to speed the initial build phase and significantly reduce the timelines of additional development phases. From automated source to target mapping, transformational discovery, Unified Schema prototyping, Automated ETL job creation, Data lineage and Impact analysis, Metadata driven design delivers speed with accuracy.
- Flexibility – Metadata driven design promotes the creation of a flexible framework based on a set of agreed standards and reusable information assets. This provide the ability to easily and quickly analyse the impact and implement changes to add new data sources or extend the existing assents to meet new requirements.