Metadata Visualization and Discovery for JD Edwards
Safyr® for JD Edwards Metadata Visualization and Discovery – powerful exploration software to access, understand, subset and share your JD Edwards tables, attributes, relationships and more.
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 to optimize value from JD Edwards data for digital transformation
“We have begun efforts to assess the current state of particular areas of our data and have used Safyr to help us understand the intended purpose of certain fields in the system and compare that to how they are being used or misused in the system. This will help us to identify areas of opportunity to better leverage the system as intended”
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.
These are:
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.”
Safyr reveals details of all the tables in the JD Edwards EnterpriseOne database, including any added by the user.
It’s easy to search the tables, either using the ‘technical’ name (e.g. F0101) or the ‘descriptive’ name (e.g. Address Book master) and to see the numbers of relationships to other tables in the system, and the number of Rows in each table.
Each table can be expanded to show all the Fields, the Primary Key and Foreign Keys and a detailed description of each Field, all based upon the definitions in the JD Edwards Data Dictionary.
Safyr works out EnterpriseOne Relationship information by looking at Business Views to derive joins. A range of features are also available for creating relationship definitions. Using this information, details of the related tables for a given table can be displayed. In addition, its easy to filter out any of the related tables that do not contain data.
As well as seeing tables in list form, Safyr provides a Hierarchy of JD Edwards EnterpriseOne modules, grouping the Tables by business areas like Accounts Payable, General Accounting and Address Book.
Tables can be grouped into Subject Areas with Safyr and then visualised as an Entity Relationship diagram, either using Safyr’s built-in ERDiagrammer, or a range of popular data modelling tools including ERwin, ER/Studio and PowerDesigner.
An accurate and relevant JDEdwards data model will often be an important step in understanding JDEdwards data. Request a JD Edwards Data Model that best fits your requirement.
Not only does Safyr let you browse and build your own Subject Areas, but we deliver a collection of pre-built Subject Areas based upon popular grouping of JDEdwards Tables. These give users a fast-start to quickly identifying tables for key business domain areas. These include, Sales Order Processing, Time Accounting, Expense Management and many more.
We can help with your Business Case for Safyr.
Watch this short video to get an overview of the features Safyr provides for exploring JD Edwards Enterprise One metadata.
For more information please contact us, book a call or demo or get your free trial of Safyr.
For further information, read our blog post: How well do you know your JD Edwards data?