Transitioning to Azure Data Lake extract for D365 F&O
In my previous blog, I mentioned several areas where D365F&O Customers could benefit from using Azure Data Lake Extract to support more reporting and analytics use cases. You can read that blog here: How Azure Data Lake is releasing additional value for organisations with D365 F&O, but in summary, Azure Data Lake extract provides D365F&O customers with;
- Enhanced Data Availability
- Increased Data Frequency
- Better reliability and ease of setup
- Support for more advanced use cases
While working with customers at various stages of their transition journey to Azure Data Lake with D365F&O, several common themes are emerging;
Pilot – select one or two high visibility reports to use for a pilot to prove the process and showcase the enhanced capabilities. By selecting high visibility reports, and potentially enhancing the report capabilities through additional data or increased refresh frequency, customers can start to socialise the enhanced capabilities of data lake compared to legacy approaches. The reports selected should be complex enough to act as a basis for defining a design pattern to transition future reports to data lake
Plan – analyse data used in reports to determine scale of data needed to transition all reporting to data lake. Depending on the scale of your reporting on D365F&O, this plan could be extensive and take some time to complete. The transition plan should be designed to release value as early and as frequently as possible. Defining a sprint based delivery plan to execute the transition is an effective approach we’ve seen work well for large scale transitions.
Automate – depending on your organisational data engineering capability, the landing of data into the data warehouse could be automated to provide a ‘single click’ provision of data from D365, through the Data Lake into the Data Warehouse staging area. At this point it can be modelled and surfaced to support reporting, or provided in it’s raw form to allow analysts and business users to perform discovery on new data being made available.
Delivery Model – if your organisation is currently operating a ‘corporate BI’ delivery model, where all reporting is done by the IT team, this could be an opportunity to move to a more hybrid model where business users are provided with access to more ‘raw’ data to support prototyping bringing new data in to existing reports, or completely new data sets that aren’t yet available in the data platform. Putting data in the hands of capable business users will supercharge your reporting delivery model, but governance needs to be front and centre to make sure the single version of the truth is maintained and trust in the insights is assured.
Whilst the considerations when transitioning to Azure Data Lake Extract for D365F&O are largely technical in nature, they do offer up several opportunities to drive adoption and gain business buy in which can provide overall benefit to Data & Analytics in your organisation.
Inciper are currently supporting several customers on their transition to Azure Data Lake for D365F&O, please get in touch if you would like to discuss the benefits it could provide your organisation.
