The most sustainable and cost-effective solution for knowledge management is to create a data warehouse (DW) between systems and reporting. A data warehouse is often perceived as something that’s expensive to make and maintain. Anything done wrong is expensive and inefficient. A well-designed data warehouse, on the other hand, is the cornerstone of the entire knowledge management process, saving resources and costs immediately, not to mention in the longer term. Without a good data warehouse it is difficult to address data quality effectively. Without good quality data you’re just getting the notion of managing with knowledge, but it’s really just guesswork.
In this blog post, I have summarized a list of the benefits of a high-quality data warehouse.
Immediate benefits
- Reporting does not use the resources of the source systems, as data transfers to the data warehouse are usually scheduled to take place at night.
- Data retrieval can also be automated from files (e.g. budgets from Excel) and the web (e.g. Statistics Finland).
- The data are validated before it is released to the data warehouse, and incorrect data are placed in a monitoring report. When the incorrect data are amended in the source system, they also enter the data warehouse.
- Calculations are done only once, and not separately for each report, which means that it’s cost-effective to produce and maintain, and the reports are generated quickly.
- Data aggregation is performed automatically. Example: Information about the customer is found in several places, such as CRM, ERP, etc. The data warehouse collects customer data from all of these, and provides a single view of the customer regarding bids, sales history, satisfaction, etc.
- This saves time and makes work more efficient by eliminating costly and error-prone data copying and manual reporting. Any reporting application can be used on top of the data warehouse, e.g. Power BI.
Longer-term benefits
- Data are preserved even if the systems (e.g. ERP) are replaced. The new system is simply added to the chain. All reports are functional all the time, and there is no need to export historical data from the old system to the new system.
- Easy to expand as the business grows. For example, data (even historical) from an acquired company can easily be incorporated into reports by linking its system to the data warehouse.
- AI-based predictions can be automated in production, by integrating the process into a data warehouse.
- The data validated by an open and documented data warehouse, i.e. the actual truth, can easily be integrated into other systems. A data warehouse can therefore serve as a centralized source of data integration, thus significantly reducing the number of integrations.
So my advice is that no matter how beautiful a house is, you shouldn’t buy it if it’s built on sand.
Read more:
A data warehouse helps you move from searching for information to working with information
User-centric reporting is an effective way to communicate
Aiming for effective reporting – how to move from searching for information to working with information?
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