What are some common OLAP cube design mistakes and how to avoid them?

2 Mistake 2: Choosing the wrong storage mode

OLAP cubes can be stored in different modes, depending on how the data is processed and accessed. The main storage modes are MOLAP, ROLAP, and HOLAP. MOLAP stands for multidimensional OLAP, and it stores the data and the aggregations in a proprietary format. ROLAP stands for relational OLAP, and it uses the relational database as the source of data and performs the aggregations on the fly. HOLAP stands for hybrid OLAP, and it combines the advantages of both MOLAP and ROLAP. Choosing the right storage mode depends on several factors, such as the size and volatility of the data, the frequency and complexity of the queries, the available resources, and the performance trade-offs. For example, MOLAP offers the fastest query response, but it requires more storage space and processing time. ROLAP offers the most flexibility and scalability, but it may suffer from slow query performance and network latency. HOLAP offers a balance between speed and freshness, but it may increase the complexity and maintenance of the cube.

4 Mistake 4: Neglecting the cube partitioning and aggregation design

Another important aspect of OLAP cube design is to optimize the cube partitioning and aggregation design, to improve the performance and manageability of the cube. Partitioning is the process of dividing the cube data into smaller and more manageable chunks, based on some criteria, such as time, geography, or business unit. Aggregation is the process of pre-calculating and storing some of the common or frequent queries, to speed up the query response time. Both partitioning and aggregation can have a significant impact on the cube processing time, query performance, storage space, and maintenance effort. Therefore, it is essential to plan and design them carefully, based on the characteristics and usage patterns of the data. For example, you can partition the cube by month or quarter, to facilitate incremental processing and archiving. You can also design the aggregations based on the query workload analysis, to cover the most frequent or important queries, without overloading the cube with too many or too large aggregations.

5 Mistake 5: Forgetting the cube security and documentation

The last but not least mistake in OLAP cube design is to forget or neglect the cube security and documentation. Security is a vital aspect of any data-related project, especially when dealing with sensitive or confidential data. You need to ensure that your OLAP cube complies with the data protection and access control policies of your organization, and that you implement the appropriate security roles and permissions for your users and groups. Documentation is also a key element of any OLAP cube project, as it helps you maintain, troubleshoot, and improve your cube, as well as communicate its features and benefits to your stakeholders and users. You should document your OLAP cube design, including the business requirements, the data sources, the storage mode, the dimensions, the measures, the partitions, the aggregations, the security roles, and any other relevant information.