Cadran Consultancy has over 20 years experience with Oracle JD Edwards and has a team of more than 60 consultants. Therefore, a lot of knowledge is available on JD Edwards processes and how data is entered in the system. Just as important is the question: how do you get the data out of JD Edwards and make optimal use of it? At Cadran Analytics, we believe that Tableau is the answer to this question.
A set of dashboards provides a good starting point for developing your Business Intelligence on JD Edwards. The most commonly used modules of Finance, Logistics, Manufacturing and Service Management as well as the CTRM module developed by us for trading and risk management (CTRM) are accessible. In addition, a number of dashboards have been developed for the ICT department for tasks that can be related more to JD Edwards’ system management. A single powerful dashboard has been built for each component, visually displaying the most important metrics and key figures, capturing the essence of each module.
Insight into outstanding open invoices, payment behavior, balance sheet, profit and loss, and fixed assets, but also into current and future cash flow. What is the return of investment?
Insight into turnover, sales, revenue, stock, but also predictions about the behavior of your customers. Which articles perform well? Which don’t? How are your suppliers performing?
Insight into the performance of JD Edwards as an application. Where are the peaks in running batch processes? Which users are active in the system, when are they active, and for how long? What is the status of OMW projects and how long is their running time?
The data is pulled from the JD Edwards database and loaded into Tableau. This is called the ETL process, which stands for Extract, Transform & Load. The frequency with which this happens can be adjusted per dataset. Tableau does not directly stress the operational database and this provides good performance for the users both in Tableau as well as in JD Edwards. Tableau users are by no means always JD Edwards users (such as management and representatives), so the user population and security are also arranged separately.
A loading date / time is also included in each dataset, so that you can quickly see when the data was last refreshed. Loading the data can be either complete or incremental (only the changes compared to the previous time).
It is technically possible to reuse the security that has already been set up in JD Edwards within Tableau. Yet we did not choose this in our solution for a number of reasons. First of all, a Tableau user is not necessarily a JD Edwards user. Think of the board members and sales representatives. In addition, the administrative segregation of duties, which is necessary in an ERP system, does not always apply to a BI solution. Think of separating the entry of a purchase voucher versus the execution of the payment. In JD Edwards these functions are probably separate. In Tableau, both functions are allowed to view both outstanding invoices and payment history. It is also feasible to arrange that a particular sales representative only sees the data of his own customers.
I regularly get the question whether the JD Edwards data dictionary is reused. Again the answer here is no. Conversion of numbers with the correct decimal places is done in the ETL layer. Amounts and prices usually have fixed decimal places of two and four, respectively. Quantities is a different story. One JD Edwards implementation uses three decimal places there, while another uses none. All quantities in the ETL layer are therefore divided using a variable parameter, which can therefore be set correctly once per JD Edwards environment and all quantities come through correctly. Reuse of descriptions of, for example, category codes is also avoided. This is simply because customers in a BI solution sometimes really want to use different field descriptions than are shown on a screen in JD Edwards.
With the above, a powerful foundation has been laid, with which the standard modules of JD Edwards in Tableau are accessible. However, if customization is also present in your system, it is relatively quick and easy to add this to your Business Intelligence.
Opening up other data sources in your organization and combining them with data from JD Edwards is also very feasible.
As a Senior BI Consultant at Cadran Analytics, Rick is highly specialized in Tableau.