The two main reasons you might create a report or dashboard are: Operational or Analytical.
The table below shows the key differences between these two types of content. You may be surprised to see there is little overlap, perhaps the reports have been built on the same underlying data, in the same domain and potentially developed using the same technologies, however their purpose and audience are different.
Operational reporting supports a business process, for example, a list of calls a salesperson needs to make. They are key in the daily running of an organisation.
Analytical reporting measures or predicts the performance of something, for example, displaying your sales Key Performance Indicators (KPIs) or Metrics of staff performance, such as the number of sales against targets. They are key in understanding the health of your organisation over time.
| Operational Reporting | Analytical reporting | |
|---|---|---|
| Granularity and volume | Quite detailed, often containing long and wide datasets | Normally aggregated, summarised, includes data over time |
| Validity | Current records | Includes historic records |
| Frequency | Minutes or hours | Daily, weekly, monthly |
| Location | In the system used for the business process or an operational data store. | In a datawarehouse and data marts |
| Audience | Clerk, administrator, operator, processor | Manger, executive, decision maker |
There are differences in every category, in the real world it’s not as straightforward. There are roles within your organisation that will consume both types of content and you may want to display analytical content within an operational process, for example, showing sales staff a customer’s buying trends over time, or predictive models to classify and prioritise sales opportunities. Knowing the distinction is important.
Operational vs analytical reporting overview
Operational reporting
Operational reporting supports a business process, the best place for this is within the operational system where the process is being performed, such as a Customer Relationship Management system (CRM). Many of your business systems will offer this reporting capability:
- Providing a good user experience (information presented where needed)
- Reducing complex integration
- Allowing the data to be fresh (real-time)
Where multiple data sources are needed or application reporting capabilities do not provide the functions required, you’ll need an Operational Data Store (ODS), essentially a replication of data from your source systems into a datastore for reporting, allowing you to:
- Integrate data from multiple sources
- Utilise purpose built reporting applications
- Use it as a source for a data warehouse
- Alleviate load from the source system
Whether reporting directly on top the business application or storing information in an ODS, the data will be updated frequently and stored to a low level of granularity (individual line items).
The records of data in this datastore are often current values but can represent any data in the source business application (where some historic records may be stored). The ODS will not hold (persist) data that does not exist in the source system. As this data set is essentially a replication of data from the source, it’s relatively simple to implement, and quick to update.
Analytical reporting
Your analytical reports focus on measuring past performance and predicting future trends, giving you the information needed to drive your strategy and objectives.
The data that feeds these may contain complex calculations, come from multiple business systems, be tracked over time, and evaluated against targets. You will want to drill through this data, slice and dice it in order to give context.
Analytical reporting contains more manipulation than operational reporting, it focuses on measuring and aggregation.
Data warehouses (DWH) exist specifically for this type of analytical reporting, they are a database designed, prepared and optimised for analytics. A data warehouse often includes Data Marts, these are a subset of the data warehouse focused on specific subject areas, guided by business analytical needs, for example, Sales analysis or Marketing analysis.
The advantages of using a data warehouse and data marts as the source for analytical reporting include:
- Keeping history of data changes over time
- Consistent calculations and measures
- Organised for ease of use
- Controlling and highlighting data quality
- Designed for quick, performant access
Recognizing the difference between analytical and operational reporting will help you find a solution that’s fit for purpose, sustainable and gives a good user experience.
