Trying to get a comprehensive and accurate picture of your JD Edwards data is a bit like attempting to complete a jigsaw puzzle without being able to turn over the pieces to see their individual colours and how they relate to each other. It takes ages and the results are probably wrong!
This blog covers the 3 challenges you face when trying to get to know and utilise your JD Edwards data. It will also show you how you can use Safyr to overcome those challenges and get more from your JD Edwards data.
- Where can you find out where the JD Edwards data you need is located?
- How do you find the data that really matters for your project?
- How do you use that information in other tools to support your project?
Why do you need to understand your JD Edwards data and data model?
Almost every data-oriented project you undertake will require you or your team to be able to access and make sense of the metadata in your JD Edwards system. For example, imagine trying to determine which tables from JD Edwards hold the data you need for your data warehouse or analytics project.
Which tables are needed for your data governance or catalog project? Where are the tables which contain sensitive personal data or personally identifiable data to help you meet privacy and compliance requirements?
If you cannot access, analyse and share your JD Edwards metadata quickly and easily then you run the risk of projects being delayed or experiencing cost overruns. You also be inadvertently introducing inaccurate data into your information ecosystem.
Where can you find the JD Edwards data you need?
To answer this question, you need to be able to understand the metadata in your JD Edwards system. Unfortunately, this is not a straightforward task.
There is no useful metadata in the JD Edwards database system catalog. Here is an example of what information you will find there.
As you can see this is of no help at all, unless of course you happen to know what these tables and attribute names mean. Most people don’t.
You can also see that there is no way of determining whether and how these tables may be related. This is especially important if you are planning to use them for reporting, data architecture, master data, data catalog or other projects.
So where is the metadata? The really useful metadata including table and attribute names you can relate to are in a series of data dictionary tables. They also contain any customisations your organisation has made to enhance the standard system and reflect the particular needs of your business.
If you can access these data dictionary tables you have access to metadata which makes sense and can be understood by your data architects and analysts.
You use Safyr® to connect to the data dictionary tables and extracts the metadata it finds there. This includes all customisations so you can be sure that you are working with the metadata in your system, as implemented.
Using Safyr means you can see what data the tables contain and how they are related. This is how Safyr displays the tables F4201 and F4211.
As you can see this is much easier to understand. Using Safyr means that you now know that F4201 is the Sales Order Header File table and F4211 is the Sales Order Detail File table. Safyr also shows you how the two tables are joined on the fields Order Number, Order Type and Order Company. It is also simple to relate to the content in the rest of the Table fields.
How do you find the data that really matters for your project?
You may have tried to try to find the JD Edwards data you need for your project using traditional, manual methods, employing external consultants or your own internal specialists. You may have used other software solutions which work from templates derived from the basic JD Edwards system as delivered.
These usually take more resource in terms of time and cost than anticipated.
Safyr offers you an alternative approach which accelerates the process of finding the metadata you need for your project. Once the metadata is extracted into a Safyr repository you have a range of functions and tools you can use to navigate and explore the metadata using business English terms.
The first step is to connect Safyr to your implementation of JD Edwards and extract the metadata it finds there, including customisations. Then you can easily get an overall view of the tables it contains.
This view shows you that this instance of JD Edwards has 4,525 tables. You can also see the Description for each table, how many tables it is connected with and how many rows each table contains.
But of course, that is too many tables for you to scroll through in the vain hope that you will stumble on something you are looking for. So, Safyr provides you with a couple of ways of searching for tables. You can search by typing in part or whole of the tables name in the Table Name search box or provide some text in the Short Description search box.
In the screenshot below you can see the results of searching for Tables which contain F4201.
Once you select the table you are interested in you can see the details of all its attributes and also the other tables to which it is connected in the screenshot below. This includes Table F4211 which was also relevant to the original question. Obviously, there are other related tables in which you might be interested.
Then it is simple to create and export a data model of the two tables. All you need to do is to create and name a new Safyr Subject Area and add the relevant tables to it (see screenshots below).
How can you use that information most effectively for your project?
You can then export the Subject Area to a variety of different 3rd party software products and industry standard formats. You may want to export those Subject Areas into a data catalog tools such as Collibra, Informatica EDC, Alation or Infogix.
You may want to export the relevant tables into a data modeling tools such as ER/Studio or erwin to then use their capabilities to create a data warehouse schema.
One example of how the tables can be represented in an Entity Relationship Diagram is included above. One of the other export formats is to an Excel spreadsheet which is shown below.
Want to find out more?
If you think Safyr could help you to accelerate JD Edwards data discovery for your projects and would like to know more, please select one or more of the following options.
There are also a number of videos which illustrate how Safyr works. You can view a short introductory video which demonstrates Safyr working with JD Edwards.