Still waiting for your data warehouse?
Organisations are becoming increasingly aware of the value of data, and how it can be used more extensively to inform decision making and achieve business objectives. However without the ability to wade through large volumes of data, interpret, understand, and apply it, the data itself is useless.
A solution to this problem is to create an easily accessible repository of useful and accurate “customer” (this covers all manner of people e.g: constituents, claimants, prospects...) information using the data from existing company databases, which is stored in one place. The question is in what form should this repository be built – a data warehouse or a datamart?
What’s the difference?
A traditional data warehouse is a single enterprise-wide solution, designed to serve the needs of the entire organisation by storing vast amounts of data on all aspects of the business in one place. A datamart is a smaller scale, more modular solution, which focuses on specific subject areas or business functions – like marketing.
A data warehouse is the ideal solution, with all the information stored in one place and the entire organisation benefiting from the knowledge in it.
Smaller scale datamarts are easier, faster (months verses years for a data warehouse) and cost less to build and implement than a data warehouse. They deliver value and ROI almost immediately. Datamarts can also be used as a stepping stone to a data warehouse - providing accessible, usable and accurate data while a data warehouse is being built in the background. Once the initial datamart is set up it can be expanded to include additional datamarts, user-friendly reporting, or campaign management solutions for a more informed and co-ordinated approach to solving business and marketing problems.
However, both have their drawbacks.
Data warehouses are complex. They require company-wide buy-in and input from the entire organisation, they’re expensive and tend to take a long time to develop and implement. Many New Zealand businesses have had data warehouses on their wish list, or as work in progress, for many years.
There is a risk of departmentalised datamarts, which have been built independently of each other, being incompatible because of inconsistent structure. Datamarts need to be built with forethought, with a standard structure for easier integration into a data warehouse down the track. Failure to do so can leave you in a bigger mess than you were in, before you started any kind of data repository solution.
Benefits of building a data repository
Data repositories enable organisations to gain leverage from the value of their data to inform decision making, planning and develop data-driven initiatives to achieve business growth.
Datamarts are fully customised and can be installed in-house or hosted externally. The data is regularly refreshed and cleaned (daily, weekly or monthly) to provide up-to-date, current and accurate data, which organisations can use to easily track and report on the success of different initiatives to develop a continuous learning and improvement culture.
By merging different databases, organisations can understand a person’s total relationship with their company, and their current and potential value. To get an even better picture, relevant external data like Census and Quotable Value data and/or attitudinal research data can be appended.
Datamine has built datamarts for the financial services and FMCG industries, which are all hosted, managed and supported by Datamine. The datamarts are quite different in their composition and functionality, yet all provide valuable insights, which help these organisations create more efficient and effective business processes, as well as increase their business intelligence. Access to up-to-date data means our clients can complete analysis more efficiently and cost effectively.
Here are a few examples of projects and reports that can be generated using a datamart:
- A holistic view of a person’s interactions with your organisation
- Number of unique “customers”
- Segmentation
- Changes in behaviour
- Share of wallet
- Price sensitivity
- Measuring advertising effectiveness
- Outlet location planning
- Competitor analysis
- KPI reporting
Our take on it
We believe the best approach is to develop individual datamarts with the aim of integrating them into an enterprise-wide data warehouse. Adopting this staged approach means that an organisation can benefit from the immediate delivery of information and ROI from the datamart, while in the background a large-scale data warehouse can be created.