The cost of data warehouse maintenance is one of the barriers that must be overcome before the long-term benefits of a reporting and analytics environment can be realised.
However, most data practitioners are largely unaware of the many variables that contribute to the total cost of a data warehouse’s operations over the system’s lifetime, including:
- Acquisition costs associated with evaluating and buying hardware, storage, software, and network connectivity
- Deployment costs such as project planning, oversight and management, system design, development, configuration, testing, and implementation
- Data development and management costs, including data extraction, design and development of data integration applications, and design and implementation of data warehouse schemas
- Business opportunity costs incurred when the business is impacted by delays in getting the system running
- Operations and maintenance costs covering power, cooling, space, and telecommunications
- Recurring costs such as software license maintenance, system upgrades, and coverage for data archiving, data backup, recovery, and disaster planning.
Different organisations may have variable tolerance for these different cost categories. More established businesses may be willing to make the capital investment in infrastructure, knowing that the long-term benefits outweigh the start-up costs. Small or new businesses might not have sufficient capital reserved to pay the recurring costs over an extended timeframe yet may desire a short time to value.
Our experience at Datasync across many projects is that developing a cost model is fundamental to balancing how key expenses impact time to value. Use the cost model to determine when cloud-based data warehousing makes the most sense. In some cases, the cost of acquiring and managing the system may be spread across several projects by leveraging the platform for other enterprise data related tasks.
Alternatively, the agility of a managed system may pay off—if you can drive additional revenue six months earlier by using a cloud-based system, the increased revenue may more than offset the capital investment of a system acquisition.
With a firm understanding of your data warehouse platform cost model you can more confidently bring cloud into the platform and use it to drive incremental business value.