EDMCS and Data Governance – Part 3

Welcome to Part 3 – the finale – of the blog series “EDMCS and Data Governance!”

Part 1 provides an introduction and primer for data governance workflows in Enterprise Data Management Cloud Service (EDMCS) which was introduced in the 19.02 release.

Part 2 discusses Workflow Stages in greater detail and dives into the brains of EDMCS workflows – the Approval Policy. Approval policies at different levels of the data chain are explained, and we conclude by building a sample workflow at the dimension level.

In Part 3, I’ll attempt to tie a bow around everything and offer some parting thoughts.

Recap

As I continue to explore and learn about collaborative workflows in EDMCS, these are the key points that come to mind:

  • Emphasize the Fundamentals – No matter what tool you are using, People and Process are extremely important in any data governance solution along with strong executive sponsorship and robust change management.
  • Build the Foundation – get the client comfortable with the tool and content before you introduce workflows. A strong foundation (your applications, dimensions, views, and viewpoints) is needed before you start the plumbing and wiring (workflows).
  • Brush up on Security – I haven’t discussed security extensively in this blog series, but the Oracle EDMCS User Guide does a nice job describing security requirements for assigning and approving workflow requests. Note that security enhancements have been introduced along with workflows. A new “Submitter” permission is now available to go along with Owner, Data Manager, and Browser. And permissions can be assigned at the Application, Dimension, Hierarchy Set, and Node Type levels.
  • Ponder the Approval Policy – this is the most interesting one to me. As we discussed in Part 2, approval policies can be defined at 4 points in the data chain (see Figure 1). With the inheritance and inter-dependencies of approval policies across the data chain along with the actions each policy can govern, it is critical to efficiently design your approval policies up front.

o   For example:

  • Suppose your client requires a final “audit” type of approval across the board for any type of request for any dimension. Or they always a require an upfront “gatekeeper” type of approval to make sure the request is justified and complete before it continues down the approval chain. These would be good candidates for an approval policy at the Application level. And it would avoid having to define duplicative approval policies at lower levels in the data chain.
  • Will your application contain dimensions that do not need data governance workflows? Then Application level approval policies should be avoided.
  • Say you want to limit and govern the actions of a specific group so it can only work with existing nodes (insert, remove, update). An approval policy at the Hierarchy Set level is probably best.

o   Overall, I believe approval policies at the dimension level are a good place to start. Then as the workflows evolve and requirements become more clear, you can determine if there are common factors across all dimension approval policies that can be consolidated at a higher level (Application level approval policy), or if there are specific subsets of actions that need to be broken out to a lower level (Node Type or Hierarchy Set level approval policy).

o   All of which brings up another interesting point: effective approval policy design directly ties into effective viewpoint design. Think about it – you can define the set of Allowed Actions (Add, Insert, Move, etc.) at a Viewpoint level. Which means what? Special-purpose maintenance views are likely required to support certain approval policies, especially those at the Node Type or Hierarchy Set levels.

Figure 1 – Approval Policies and Data Chain

EDMCS and Data Governance – Part 3 - Image 1

How do EDMCS Workflows Compare with DRM/DRG?

I was reluctant to include this section at first because in general, I don’t like comparing Data Relationship Manager (DRM) and EDMCS. Yes, they are both master data management tools and yes, they do share some common concepts and terminology. But overall, the two products are so different in terms of philosophy, deployment design, and underlying architecture that I think comparing the products is often less than helpful.

However, with data governance and collaborative workflows, I feel there is enough commonality that it is worth highlighting a few items. So here goes:

Topic DRM/DRG EDMCS
Workflow Design
  • Based on workflow models and workflow tasks
  • Tasks linked to specific actions (Add Leaf, Add Limb, Insert, Move, etc.)
  • Based on Approval Policies
  • Approval policy level (Application, Dimension, Node Type, Hierarchy Type) determines context and scope of actions governed

 

Workflow Stages
  • Use a Submit stage, a Commit stage, and optionally, one or more Enrich and/or Approve stages
  • ·Use a Submit stage and (implied) Commit stage
  • Approval policies determine approval stages (sequential vs parallel, # of approvers)
  • Requests can be re-assigned for collaboration prior to Submit
User Interface (UI)
  • Form-based design
  • No forms
  • Requesters and approvers interact directly with the viewpoints
Approval Options
  • Support Approve, Reject, and Push Back
  • Support comments, narrative, attachments
  • Support Approve, Reject, and Push Back
  • Support comments, narrative, attachments
Escalations
  • Requests can be escalated based on defined intervals
  • Requests can be escalated based on defined intervals
Separation of Duties
  • Workflows can be configured to prevent a submitter from approving their own request
  • Workflows can be configured to prevent a submitter from approving their own request
Email Notifications
  • Generates email notifications
  • Generates email notifications
Other
  • Supports conditional workflows
  • Supports splitting of requests based on pre-defined criteria
  • Not yet supported

I’m curious if Oracle will introduce a form-based UI for workflows. Part of me would very much like to see that so that you can present a clean user interface to the approvers, hide unnecessary details, and display special instructions and messages, but part of me does not. One of my favorite features of EDMCS is the visual highlighting of pending request changes and the “shopping cart” of request items that are displayed prior to submitting a request. I would hate to lose that by going with a forms-based workflow UI, but perhaps there is a solution that combines the best of both worlds. 

Conclusion

Well that’s it, an initial look at workflows and approval policies in EDMCS. I’m excited to see how this functionality evolves and expands over time. Talk to you next time!

And don’t forget to follow me on Twitter (@kblackEPM) and check out these links for more information:

EDMCS and Data Governance – Part 2

Welcome to Part 2 of the blog series “EDMCS and Data Governance!”

Part 1 provides an introduction and primer for data governance workflows in Oracle Enterprise Data Management Cloud Service (EDMCS) which was introduced in the 19.02 release. This exciting feature addresses a major gap in EDMCS as the product continues to rapidly evolve and mature.

In Part 2, we dive into the details of how to configure workflows. This process revolves around the concept of an “approval policy.” Interestingly, approval policies can be configured at different points of the EDMCS data chain and cascade or inherit to affect downstream points of the data chain.

Workflow Stages

Before we dive into approval policies, let’s discuss EDMCS workflow stages a bit more. They are similar in concept to Data Relationship Governance (DRG) workflow stages. See Figure 1 for an overview:

Figure 1 – EDMCS Workflow StagesEDMCS and Data Governance – Part 2 - Image 1
  1. Submit (or Assign) Request – A request is initially created as you do today. But wait…there’s more! You can Submit the request to immediately move the request into the Approve stage OR you can Assign the request to colleagues to collaborate on the request together. When the request is ready, it is submitted to move to the Approve stage.
  2. Approve Request – The approver(s) have 3 choices:
    • Approve – the request is approved and moves forward (thanks Captain Obvious!).
    • Push Back – like DRG, the request is pushed back to the submitter for clarification or changes, who then updates and resubmits the request.
    • Reject – like DRG, the request is denied and closed. Think of “reject” as the RAID of the data governance world – it kills requests dead.
  3. Commit Request – once fully approved, the request is auto-committed and closed. EDMCS has now been updated.

Approval Policies

Now for approval policies. Approval policies can be configured at 4 levels:

  1. Application
  2. Dimension
  3. Node Type
  4. Hierarchy Set

It is important to note that each data chain object can contain one, and only one, approval policy. However, approval policies have a cascading impact so that multiple approval policies can work in concert to govern and control exactly what you want. Yes, you heard that right:  Approval Policy Inheritance – it’s not just for properties anymore!

The types of actions governed by an approval policy depend on the data chain object it is configured with – see figure 2 below:

Figure 2 – Approval Policies and Data Chain

EDMCS and Data Governance – Part 2 - Image 2As you can see, policies defined at the Application or Dimension level govern all actions (add, delete, insert, remove, move, etc.) while policies defined at the Node Type or Hierarchy Set level govern a subset of actions. Why is this important? Because it means you need to carefully design what types of actions you want to govern and who will perform them. If I define an approval policy at the Hierarchy Set level and then submit a request that Adds 3 accounts, how many approvers are required for the request? A big ZERO! Since I requested “add” actions and only have an approval policy at the Hierarchy Set level, no applicable approval policy exists to govern the request.

Putting It All Together

Let’s walk through an example.

  1. Define Approval Policy

First, I will define an approval policy for the Account dimension. To do this, Inspect either the application or default viewpoint and access the Account dimension from the Definition tab. From there, click the Policies tab.

Here you will see the Approval policy for the Account dimension. Click on the Approval link to inspect the approval policy.

EDMCS and Data Governance – Part 2 - Image 3The General tab will display basic information about the approval policy. You can edit the approval policy name and description if necessary.

EDMCS and Data Governance – Part 2 - Image 4The Definition tab is where the magic happens. Select edit to update the following parameters:

  • Enabled – click this check box to enable the approval policy.
  • Approval Method – select Serial or Parallel.
  • One Approval Per Group – if using Serial approvals, this will automatically be set to “True.” If using Parallel approvals, you can select one approval per group or define a Total Required # of approvers.
  • Include Submitter – enable this to allow the submitter to also be an approver (the submitter’s approval will be automatically granted). If “separation of duties” is required for your company, do not enable this.
  • Reminder Notification – the # of days that will elapse before reminder emails are sent.
  • Approval Escalation – the # of times a reminder occurs before an escalation email will be sent.
  • Approval Groups – select user(s) and/or group(s) to be included in the approval process. When using Parallel approvals, the order of approval groups does not matter. When using Serial approvals, the order of approval groups does matter – you need to list the approval groups in the order that approvals should be executed.

With my example approval policy, I am using serial approvals, 2 approval groups (a Planning group and GL group), a reminder interval of 5 days, and an escalation interval of 2 reminders.

EDMCS and Data Governance – Part 2 - Image 5

  1. Submit Request

Now we’re cooking with gas. It’s time to submit a request. I will submit a request to my default Account viewpoint that includes 1 add, 1 property update, and 1 move. Here is the request in Draft status:

EDMCS and Data Governance – Part 2 - Image 6

Did you notice something new? Look at the Actions button next to Submit. This is where you can assign the request to another user and collaborate with him to finish up the request.

EDMCS and Data Governance – Part 2 - Image 7

EDMCS and Data Governance – Part 2 - Image 8

  1. Approve the Request

After the request is submitted, it is considered “in flight” because it has been submitted, but not yet approved/committed. And look! EDMCS now offers a nice Activity page on the home screen displaying the status of various workflow requests:

EDMCS and Data Governance – Part 2 - Image 9

First, the users in the Planning Approvers group will receive an email notifying them that they have been “invited to approve a request” (it’s very polite):

EDMCS and Data Governance – Part 2 - Image 10

As mentioned earlier, an approver has 3 choices: Approve, Reject, or Push Back. Reject and Push Back are available under the Actions dropdown. Here are the dialog windows that will be displayed for those actions (note the comment field is required):

EDMCS and Data Governance – Part 2 - Image 11

Otherwise, the approver will click the Approve button and see this:

EDMCS and Data Governance – Part 2 - Image 12

And then the same process will continue with the GL Approvers group since I am using Serial approvals. Once again, an approver can reject, push back, or approve. Once approved, the request is committed and closed.

Congratulations! You have now completed your very first data governance workflow request in EDMCS!

Conclusion

This blog post should be useful in providing more details and clarity on workflows, workflow stages, and approval policies. In the third and final post for this series, I’ll offer a recap and some closing thoughts. Talk to you then.

And don’t forget to follow me on Twitter (@kblackEPM) and check out these links for more information:

Retro Reboot #1: Set It & Forget It – Scheduling FDMEE Tasks

As with most nostalgic items, reboots are the next best thing. From video game consoles to television shows, they are all getting a modern facelift and a new prime-time seat on television.  I have jumped on that band-wagon to revitalize a previous post authored by Tony Scalese: Set it & Forget It – Scheduling FDM Tasks.

As with most reboots, there must be flair and alluring content to capture old and new audiences. Since Oracle Financial Data Quality Management Enterprise Edition (FDMEE) has been in the Enterprise Performance Management (EPM) space for a while and has moved into the Cloud, this is a great time for its reboot!

Oh Great…A Reboot. Now What?

Scheduling tasks in FDMEE has never been easier. Oracle provides several ways to do this for a variety of out-of-the-box activities.  Is there a report that you want to run and email every hour?  Or how about a script that needs to run hourly?  Or maybe batch-automation every 15 minutes?  No worries!  FDMEE can handle all of that with out-of-the-box functionality.

Let us pause for a moment and determine what is needed to make this happen:

  1. Is there a business case and justification for what is about to be scheduled?
  2. Who benefits and how will they be notified of the results?
  3. Is there a defined frequency for which the activity must take place?

Getting Started

First, understand that the scheduling for FDMEE is built directly into the Graphical User Interface (GUI) anywhere you see the “SCHEDULE” button. Unlike the previous FDM counterpart which had it as an independent utility to be installed/configured, the ease of having it via the Web has removed some complexity.

A word of caution:  while this screen allows items to be scheduled, there isn’t a screen that shows “what has been” scheduled.  To do that, access to the Oracle Data Integrator (ODI) is needed, but more on this later.

Initially, the screen shows the types of schedules that can be created and their relevant inputs.

Retro Reboot Screen Shot 1

Below is a reference guide to outline FDMEE’s scheduling capabilities.

Schedule Type Inputs Notes / Examples
Simple TimeZone, Date, HH:MM:SS, AM/PM Single run based on the specified inputs.

 

Example:  Run 08/02/2018 @ 11AM

Hourly TimeZone, MM:SS Repeatable run at the specified time MM:SS time.

 

Example:  Run every hour, at the 22minute mark.

Daily TimeZone, HH:MM:SS, AM/PM Every day at the specified time.

 

Example:  Run every day at 11AM.

Weekly TimeZone, Day of the Week, HH:MM:SS, AM/PM Every specified day at the specified time.

 

Example: Run every Monday thru  Friday at  11AM.

Monthly
(day of month)
TimeZone, Date, HH:MM:SS, AM/PM Specified day at the specified time.

 

Example: Run on the 2nd day of every month at 11AM.

Monthly
(week day)
TimeZone, Iteration, Weekday, HH:MM:SS, AM/PM Specified interval and week day at the specified time.

 

Example: Run every third Tuesday at 11AM.

Why Does the Job Run Under My UserID?

That is because the system assigns the user’s credentials who created the schedule. What can go wrong with that, right?!  Well, if a user no longer exists or a password is changed, the existing jobs will no longer run.

The following considerations should be observed:

  1. Dedicate a service account that is not being used by an employee to be used for server/automation actions.
  2. This account can be a “native” user; since the account is only used internally for EPM products, having a domain account is not needed.
  3. Non-expiry passwords are best.

 It is Scheduled…Now What?

After the item is scheduled, what really happens? The action executes at the scheduled time!  Actions can easily be monitored via the FDMEE Process Details screen.  Now all the possibilities of scheduling the following can be explored:

  1. Data Load Rules
  2. Script Executions
  3. Batch Executions
  4. Report Executions

Also, as mentioned earlier, there is no way to see the batches inside of FDMEE. For that, information can be retrieved in a few ways.  The easiest way to see what is scheduled is to use the ODI Studio.

The ODI Studio provides details as seen in the screen shot below:

Retro Reboot Screen Shot 2

Any scheduled tasks will be listed under “All Schedules.” Simply double click them to obtain details related to that task.

Retro Reboot Screen Shot 3

Another effective option is to write a custom report that displays the information. My previous blog post, Easy Value with FDMEE Reports, provides further details of FDMEE report options and their value.  This would allow a report to be executed to provide a user-friendly report.

Seriously … What Now?

By now, you may have noticed from the previous blog post Scheduling FDM Tasks – A Second Option by Tony Scalese that the upsShell process is quite handy.  It allows other tools to control the FDM jobs…maybe through a corporate scheduler.  Now that most organizations have a corporate scheduler, the new FDMEE options below must be learned:

Command Purpose
Executescript.bat / .sh Executes an FDMEE Custom Script
Importmapping.bat / .sh Executes an import from text-file for Maps
Loaddata.bat / .sh Executes a Data Load Rule
Loadhrdata.bat / .sh Executes an HR Data Load Rule
Loadmetadata.bat / .sh Executes a Metadata Load Rule
Runbatch.bat / .sh Executes a defined Batch
Runreport.bat / .sh Executes a defined Report

*All files are stored in the EPM_ORACLE_HOME\products\FinancialDataQuality\bin\

In the example below, the command, when launched, executes a Data Load Rule for Jan-2012 thru Mar-2012:

Retro Reboot Screen Shot 4

There still must be a better solution…right? Things to overcome:

  1. What happens if the scheduler is Windows-based and the server is Linux?
  2. How does a separate scheduling server communicate with EPM? Does it have to be installed on each EPM Server?
  3. How can we monitor and get details of a job once it is kicked off?

What Happens if You Don’t Want to Run the .BAT/.SH Files?

You’re in luck! With the introduction of new functionality to FDMEE, RESTful APIs are also now available.  With the RESTful APIs, not only can you execute a job, but you can also loop and monitor for the results.  This enhances the previous .BAT/.SH file routines and provides a cleaner and more elegant solution.

Command Purpose
Running Data Rules Execute a Data Load Rule
Running Batch Rules Execute a Batch Definition
Import Data Mapping Import Maps
Export Data Mapping Export Maps
Execute Reports Execute a Report

*URL construct: https://<SERVICE_NAME>/aif/rest/V1

The below example is just querying for a process:

Retro Reboot Screen Shot 5

The Future…

As Oracle moves forward to enhance the RESTful APIs, many doors continue to open for FDMEE and tool scheduling. At Edgewater Ranzal, we fully embrace the RESTful concept and evolve our solutions to utilize this functionality.  The result is improved support and flexibility of FDMEE and the future of Oracle Cloud products.

Contact us at info@ranzal.com with questions about this product or its capabilities.

The Data Governance Triple Crown

A few weeks ago, those who follow horse racing witnessed a historic event. The race horse Justified captured the Triple Crown by winning the Belmont Stakes following earlier victories in the Kentucky Derby and Preakness Stakes. Justified became only the 13th horse in history to capture the Triple Crown, and the second horse to do so in the last 4 years (American Pharoah captured the honor in 2015). Interesting side note: both Justified and American Pharoah were trained by Bob Baffert. Why does that matter? Because he’s a fellow Arizonan native and University of Arizona alumnus, that’s why! Bear Down!

While it may be a stretch, the concept of a “triple crown” of sorts has been on my mind recently as it relates to recent Oracle Enterprise Performance Management (EPM) projects I’ve been working on involving Oracle Data Relationship Management (DRM) and Data Relationship Governance (DRG). Many people are familiar with the DRG module of the DRM product, but when the tool is coupled with two other critical components, you are well on your way to capturing the Data Governance Triple Crown.

1.    Tool – Data Relationship Governance

As you may know, DRG is a module of the DRM product and provides a governance framework for maintaining your DRM master data. DRG includes functionality such as workflows, approvals, email notifications, and separation of duties (to prevent someone from approving his own request). Workflows are often structured around dimension maintenance and may include requests like “Add Account,” “Update Account,” or “Move Account.” The workflow then guides the requester to select tasks and complete fields on a data entry form. Once submitted, the request enters optional enrichment stages where additional detail and context is added to the request before finally being committed and updating the relevant DRM structures.

Here are just a few of the key features in DRG:

  • Requests can be entered interactively or via bulk upload files
  • Documents (such as supporting request documentation, emails, or policies) can be attached to requests
  • Comments/supporting narrative can be included
  • Requests can be pushed back to a prior stage, approved, or rejected
  • Request can generate email notifications to approvers and/or participants in a workflow requests
  • Requests can include validations, calculated fields, and conditional criteria to enter or bypass specific stages in the workflow

While I could go on and on about DRG, I’ve noticed a DRG implementation is most effective when paired with two other components.

2.    Process – Data Governance Program

In my experience, DRG implementations are most successful when bundled into a broader data governance program. Data governance programs bring together the Tool (DRG), the People (data stewards, data specialists, data governance council), and the Process (process flows, metrics, and standards).

Key facets to an effective data governance program include:

  • Executive sponsorship
  • Data Governance Council
  • Clear Roles and Responsibilities
  • Standards (metrics, definitions, process flows)
  • Authority and Accountability

Data governance programs are not easy! The change management aspect to implementing effective data governance cannot be underestimated. There will be natural resistance, pushback, and challenges to any type of change, and data governance initiatives are no exception. Data governance implementations require patience and perseverance, and at times, even a bit of the “carrot and stick” approach. As a result, we have seen the following steps as crucial to getting your data governance program off the ground:

    1. Define Charter Team and Responsibilities
    2. Define the Mission Statement
    3. Define the High-Level Scope
    4. Define the Terminology and Standards
    5. Define the Current State Overview
    6. Define the Future State Vision
    7. Define the Draft Phased Approach
    8. Prepare the Project Charter
    9. Present the Project Charter for Executive Approval
    10. Ensure Executive Support

While there is much more content to dive into on a data governance program that is beyond the scope of this blog, I hope you appreciate the importance of People and Process in a data governance initiative and do not focus only on the Tool.

3.    Integration – DRM to External Systems

The third and final component to effective data governance, after the Tool and Process, is integration to external systems. This allows DRM to truly become the master data hub in your company’s eco-system and systematically push master data (which could include trees/hierarchies, base members, mappings, or all of the above) to both upstream and downstream systems.

By leveraging DRM’s robust integration capabilities and adding in some custom SQL or ETL integration as needed, DRM can produce master data in various forms (flat files, SQL tables, web services, external commits) for consumption by external applications. And these integrations can be run on-demand or scheduled.

Summary

So there you have it. Three critical components to effective data governance: a good tool (DRG), a robust process (data governance program), and automated integration (with DRM as the hub).

Are any of these components effective in their own right? Certainly. Each area adds value in its own right and can be implemented standalone. But when all three components are implemented in conjunction, the whole is definitely greater than the sum of the parts. Each component presents its own set of challenges and requires close collaboration with both technical and business personnel at a customer. And executive sponsorship and buy-in is absolutely vital to managing and overcoming the inevitable change management challenges. It ain’t easy, but like the saying goes, nothing worthwhile ever is, right?

I’d love to hear your thoughts on this topic along with any best practices, lessons learned, or battle scars earned along the way. Feel free to connect with me on LinkedIn or Twitter.

Data Governance in the Cloud: An Integrated Strategy; A Unified Solution

Are you tasked with making organizational decisions that have placed you in a major dilemma? As a decision-maker in today’s fast-paced economy, you must wonder how you can cut costs, improve the bottom line, and still maintain the data quality necessary to make strategic decisions.

Take heart because it IS possible to achieve a balance of on-premise and off-premise Enterprise Performance Management (EPM) software while maintaining integrity and control of your data to provide the quality and data assurance needed for success – AND benefit financially from new Cloud technologies.

Success is a combination of understanding what each data tract requires and creating an integration strategy consisting of the necessary business processes and software tools that deliver consistency and integrity of your EPM strategic data.

Past trends called for a tight on-premise coupling of all EPM software to achieve the best results. This strategy required maintenance of a large hardware and software infrastructure and related personnel to keep everything running smoothly.  The new Cloud “POD” subscriptions are geared toward reducing the high costs of infrastructure which is a financial benefit. As in all things in life, there is a consequence of moving to Cloud technology.   An unexpected consequence of Pod technology is the creation of isolated silos of information, but there is an easy resolution!  The key to overcoming this limitation is to gain an understanding of what each component offers and demands, and creating an integration strategy to bridge that gap.

If you are interested in learning how to create this strategy to bring the various pieces together as a unified solution or if your organization plans to migrate to the EPM Cloud platform in the future, this whitepaper helps to define a process to pre-build the integration strategy and make moving to the Cloud easier with reduced time to migrate.

Download our whitepaper: Data Relationship Management (DRM) for Cloud-Based Technologies:  Using DRM for Data Governance in the Cloud

Come See Edgewater Ranzal at Kscope11

ODTUG Kscope11 is right around the corner. Kscope11 offers the chance for a full day EPM Symposium on Sunday, plus the opportunity to learn from experts in the EPM and BI fields on a wide range of topics.

Edgewater Ranzal will be well represented at the conference, with our associates presenting eight presentations covering Planning, DRM, EPMA, HFM, and FDM. The sessions that we will be presenting at Kscope11 are summarized below. Each title links to an abstract for the presentation, providing additional details.

Session No. Date Time Room Presenter Title
1 6/27/11 11:15 – 12:15 102C Jeff Richardson Calculation Manager:  The New and Improved Application to Create Planning Business Rules
7 6/28/11 11:15 – 12:15 103C Tony Scalese Planning (or Essbase) and FDM and ERPi Equals Success!
10 6/28/11 4:30 – 5:30 101B Chris Barbieri Security and Auditing in HFM
11 6/29/11 8:30 – 9:30 103A Patrick Lehner Best Practices for Using DRM with EPMA
11 6/29/11 8:30 – 9:30 101B Chris Barbieri Getting Started with Calc Manager for HFM
12 6/29/11 9:45 – 10:45 101B Chris Barbieri Advanced Topics in Calc Manager for HFM
12 6/29/11 9:45 – 10:45 102C John Martin Have it Your Way: Building Planning Hierarchies with EPMA or Outline Load Utility
13 6/29/11 11:15 – 12:15 101B Tony Scalese Maximizing the Value of an EPM Investment with ERPi, FDM, & EPMA
17 6/30/11 8:30 – 9:30 101B Tony Scalese Taking Your FDM Application to the Next Level with Advanced Scripting
18 6/30/11 10:30 – 11:30 101B Peter Fugere IFRS Reporting Within Hyperion Financial Management

In addition to the presentations above, you can catch up with our experts at our booth in the Vendor Showcase.

We look forward to seeing you in Long Beach. If you haven’t already registered, you can do so here.

Why not EPMA…who needs DRM?

Should I use EPMA or DRM?

Should I use EPMA or DRM?

Over the past several months, and quite possibly the past year or two, there have been numerous discussions regarding the need for a separate master data management (MDM) tool such as Hyperion / Oracle Data Relationship Management (DRM) to manage Hyperion metadata outside of the Enterprise Performance Management Architect (EPMA) tool that comes with Hyperion System 9 and Oracle Fusion 11.

Recently at a users’ conference, I heard comments like “EPMA is DRM ‘Light’” and “EPMA is DRM with a Web interface”.

Hyperion, and obviously now Oracle, has invested deeply in EPMA and it is difficult to identify how and where it might differ from the DRM product. Oracle has even used portions of the DRM base code and underlying architecture in EPMA and when looking at vapor-ware demos, you might draw similar conclusions to those quotes above. In reality, EPMA, in its current state, is a pumped up version of the old Hyperion HUB as it relates to metadata management. Granted, EPMA has updated the user interface leveraging the glyphs (icons) and nomenclature from DRM while completely missing the intellectual aptitude that a master data tool provides.

Below are the key uses that were provided in a recent Oracle presentation as well shows the difference between EPMA and DRM:
EPMA
  • Unifies and aligns application administration processes across the Hyperion EPM system
  • Imports and shares business dimensions in the Dimension Library
  • Builds, validates, and deploys applications in the Application Library
  • Designs and maintains business rules in Calculation Manager
  • Loads and synchronizes transaction data into and between EPM applications

DRM

  • Manages change of business master data across enterprise applications
  • Consolidates and rationalizes structures across source systems
  • Conforms dimensions and validate integrity of attributes and relationships
  • Synchronizes alternate business views with corporate hierarchies
  • Key Features include:

           i.      Versioning and Modeling
           ii.     Custom rules and validation
           iii.    Configurable exports
           iv.    Granular security
           v.     Change tracking

 *Oracle Hyperion Data Relationship Management, Fusion Edition 11.1.1– Robin Peel