Built from the bones of Dynamics AX, the cloud-based Dynamics 365 Finance & Operations (D365FO) has introduced some new out-of-the-box reporting and analytical capabilities to customers. While some functionality mirrors how it was done in Dynamics AX, there have been changes to how you create SQL Server Reporting Services (SSRS) reports, ad hoc reports, and custom reports in D365FO.
In this blog post, we are going to cover Data Entities.
What is a Data Entity?
A data entity is an extract of core data from your D365FO system. Data entities provide a conceptual abstraction of underlying table schemas which represent the common data concept or functionality, for example, Customers or Vendors. In normalized tables, most data for each customer might be stored in a customer table and then spread out across a small set of related tables.
Many data entities are aimed at specific areas for reporting. For instance, the “Customer” concept appears as several de-normalized views. Each of these Customer views contains rows of data from the customer, its related tables, and transaction tables. In this way, D365FO users end up with data entities specific to reporting needs such as customer listings, sales (invoice) reports, or open orders reports.
Data entities are extracted using Microsoft’s Data Extract Apps. They can sit inside your D365FO instance, or in a separate Azure space (BYOD – Bring Your Own Database), which stores the data entities in Azure but in a SQL format which is accessible to reporting. There are five categories of data entities based on their functions and the type of data that they serve:
- Parameter (Ex. General ledger)
- Reference (Ex. Tax Codes)
- Master (Ex. Customers)
- Document (Ex. Opening Balances)
- Transaction (Ex. Pending Invoices)
In D365FO, ad hoc reporting requires you to take the data out of D365FO and put it in de-normalized data entities. It’s the only way to get at the data.
When it comes to using data entities, you have two choices: out-of-the-box or custom data entities. Microsoft has spent a significant amount of time developing out-of-the-box data entities for you to use. There are nearly 2,000 entities available within D365FO, all of which are narrowly focused on reporting needs.
If you want to tailor your data entities to your business, most customers (and partners) must take the time to develop their own custom data entities for direct use in reporting and visualization (Power BI). This requires extracting, transforming, and loading (ETL) the data from raw AX tables (or other sources) into combined data entities tables for reporting and analytics.
4 Common Issues with Using Data Entities
Data entities join and link your data in D365FO to make it easier to write a report. While they are designed to simplify, data entities still have some kinks that need to be worked out. Here are 4 of the most common problems that D365FO customers are experiencing working with data entities:
1. Super Slow Performance
If you leave a data entity inside Azure, you are essentially creating a view, not writing a physical table. This runs through OData and is known for how long it takes to load. These performance issues can be mitigated by storing your data entities outside the box, in your own database (BYOD).
2. Costly and Time-Consuming
Even though Microsoft provides over 2,000 out-of-the-box data entities, most customers spend significant amounts of time and money to customize their data entities. This requires a new technical skill set where you likely have to hire new staff or outside consultants.
3. Accessing Up-to-Date Data
If you store your data entities in a BYOD, you will come across a problem with incremental updates. Inside Azure, you’re creating a view which can be updated with live D365FO data instantly. In a separate database, your data is just sitting there and needs to be updated. If you have to rebuild an entity to reload it for accurate data, it can take from 20 minutes to an hour, presenting a massive issue of timeliness.
4. Merging Multiple Data Sources for One Governed Data Set
Mixing historical data from Dynamics AX and live D365FO is time-consuming and highly complicated. The solution is to make the AX data available to the web for publishing, however, this requires strong technical skills in data development, which adds a lot of time to the report building process.
What Jet Analytics Brings to the Table
At insightsoftware, providing complete data access is kind of our thing. That’s why we’ve tailored our Jet Analytics solution to D365FO and started making improvements to how customers are reporting. Data entities have added a layer of complexity to self-service reporting. To lower the impact on your IT staff, we offer a different approach aimed at significantly reducing costs and time.
Jet Analytics for D365FO uses the Microsoft Data Extract Apps to create data entities on a one-to-one basis with core D365FO tables. This lowers cost by reducing the time and resources required to bring new data to use. It also supports incremental updates to keep this information current. With Jet Analytics, we provide an easy-to-setup pre-packaged set of data entities with our solution.
You also get a pre-built data warehouse and cubes (tabular or OLAP) that use these data entities to de-normalize the tables and keep all your governed data in one place. This is fully supported by incremental loading, so your data is always accurate and up-to-date.
In Jet Analytics, all your data entities will be stored in a separate BYOD, which eliminates the OData performance issues completely. Without having to sort through over 2,000 data entities and search through a dozen places, the data is much simpler for your people to access the information they need.
For more information on how Jet Analytics can simplify your D365 reporting and analytics needs, please reach out to our highly knowledgeable staff. In the meantime, download our latest whitepaper that details all of the out-of-the-box reporting and analytics features in D365FO.