Safyr® for JD Edwards EnterpriseOne
Your data analysts and data scientists can use Safyr® for JD Edwards Metadata Visualization and Discovery to gain insight into and exploit the data architecture in your own JD Edwards systems including customisations. Safyr gives them the ability to search for, find and understand JD Edwards tables and their related tables without having to know their physical names.
This is a critical task for accelerating effective delivery of a wide range of information led projects. Safyr supports you to speed up the source data discovery process for many projects such as data catalog, data governance, data warehouse, data analytics, master data, data integration, data migration and more.
Whether you are looking for a single table in JD Edwards (e.g. F9860, F42119, F0005, F0901), with its business names (e.g. Object Librarian Master Tables, Sales Order History, User Defined Code Values, Account Master) and relationships with other tables; or thousands of tables for your enterprise data catalog Safyr for JD Edwards metadata discovery will be of value to you.
JD Edwards presents you with some specific challenges when you come to try to make sense of its metadata. For example the physical names for tables and fields are particularly opaque. Both consist of codes comprising numbers and letters. In addition the relationships between the tables are not defined in the data dictionary tables. They are partially inferred from Business Views. This makes it very hard for you to navigate and make sense of the data model without a specialist tool such as Safyr.
Using Safyr with complex JD Edwards metadata modeling
“I must say that it (Safyr) has been a godsend to us for mapping out our JDE (JD Edwards) joins and business views.
The product is brilliant to say the least. I would have no issue with recommending it to anyone in a similar position.”
Customers use Safyr to solve the 3 challenges associated with JD Edwards Metadata Discovery.
Discovery: Locating the source of the useful, business ready metadata in your applications. There is very little of any value in the data system catalog. The useful metadata is in a series of data dictionary tables in JD Edwards.
Scoping and curation: Once the metadata has been located, the next challenge is to find the table or tables necessary for your task and save them for use in other tools and systems.
Delivery: The final hurdle is to provision the metadata into other tools and technical formats. These include data catalog and governance solutions such as Collibra, Informatica EDC, Alation, Infogix, ASG and Adaptive as well as data modeling tools such as SAP PowerDesigner, ER/Studio, erwin. Or you might want to use the information in Excel, CSV, XML or JSON formats.
Safyr helps users navigate the many tables and fields, not only by providing the ‘business’ descriptions for those objects, but also by interpreting the joins found in JD Edwards Business Views to give the user a means to understand the relationships between JD Edwards tables.
“It’s difficult to imagine how we could have integrated complex … J.D. Edwards metadata structures into our corporate information architecture without Safyr. The cost was low compared to other methods and a fraction of the overall project budget.”