Both operational and analytical data are crucial to business growth, but serve very different purposes.
On a basic level, operational data consists mainly of transactional data – providing the most up to date information and supporting current processes such as transactions. Analytical data on the other hand, enables sophisticated analysis on business activity, to analyze retrospectively and perform predictive analytics.
Put simply, operational data informs your business today whilst analytical data drives your business decisions of tomorrow.
What is operational data?
The data produced daily by your business systems. It provides a record of the operational business processes. This includes customer, order and inventory data, which informs the business. Operational data will be similar across organizations.
Why use operational data?
For the latest information on a single element of your business. Operational data drives daily action, providing quick updates and keeps business activities moving. This type of data remains in silos as it is specific to the function. Operational data shows the events of a business. For example, in a D2C business the stream of live data in google analytics will show website activity, behavior and transactions.
Who uses operational data?
Operational data empower teams within the business who are reactive. It’s vital for those executing the operations of the business, for example providing the list of orders which are due to ship that day.
What is analytical data?
A collection of data used by businesses to guide decision making, strategising and reporting.
Why use analytical data?
To generate a comprehensive view of the business and answer business questions. It provides business intelligence – uncovering insight from your source systems by combining them in one single source of truth. In the example of a D2C business, analytical data will show the why and how behind the activities on the website – the customer journey.
Who uses analytical data?
Business users with growth targets and an interest in understanding the past, present and future of the organization. Through analytics you can understand the why and how of operational data and optimize it.
The easy way to analysis
Building an analytics infrastructure is the first step to accessing analytical data. To achieve this, firstly a cloud data warehouse is constructed to bring all of your data sources together. Source systems provide the operational data, bringing them together in a data warehouse creates your single source of truth. Once your data warehouse is constructed, implementing a BI tool is the second step in the process, enabling the visualization of your data.
It’s near impossible to execute predictive analytics with siloed operational data. By building a data analytics stack and combining all of your data in a single source of truth you can gain more value from your data and build the intelligence to tell your business story.
Kleene makes this easy. Want to find out how? Get in touch.