Data Relationship Management (DRM) for Cloud-Based TechnologiesUsing DRM for Data Governance in the Cloud

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Data Governance

Executive Summary

This white paper gives the reader insight into a methodology to ensure that an organization maintains

orderly processes when (1) moving Enterprise Performance Management (EPM) functions from on-premise to the

Cloud or (2) preparing to move to the Cloud. It also discusses the need for data governance and the role that

Oracle’s Data Relationship Management (DRM) suite of tools plays in facilitating data governance for Cloud-based

technologies. Finally, it outlines the financial benefits and successful navigation of the perils of moving to the Cloud

as well as the threats to data quality and integrity maintenance so critical to an organization’s success.

Organizations today must face the challenges of real-time availability of quality data that can be quickly converted

to usable information to permit management to make quick and sound decisions that may significantly impact the

bottom line.

Organizations must also acknowledge that their data is as important a business asset as the products and services

they provide, and therefore must be treated with the same respect and care that is required to preserve any

legitimate business asset. Whereas in the past, companies could tolerate some laxity in data governance and

integration, the lightning world of e-commerce and mega mergers makes laxity detrimental to success.

Successful organizations must find and use the latest state-of-the-art tools and create bullet proof processes to

deal with the volumes of data collected and stored to allow all the various groups within the business to function

efficiently. Methods that provide static views are outdated and irrelevant. Coping in an environment

driven by constant change requires forward thinking and sets the stage for significant challenges. Within

the various departments of any business, manipulation and integration of data from various operational

systems must be timely and accurate to provide the differing views required for smooth business operations.

CEOs and CFOs weary of maintaining the fast-paced need for bigger, better software and hardware are moving

to Cloud services that promise to solve an array of business problems created by the changing nature of the

business. Unfortunately, movement to Cloud-based technologies has its own set of hidden challenges around

data governance and integration. Services for Oracle EPM software, or pods, are siloed environments, and

integrating them is expensive and tricky.

Cloud technologies make it difficult to force the governance required to ensure consistency and accuracy of data

across an organization. Each Cloud solution is a siloed solution that requires architecting data management

solutions, remapping data definitions, and redeployment of sources and targets. While pods can communicate on a

limited basis, the underlying integration must be properly architected and requires a tool that can seamlessly

communicate with each of the solutions. If organizations aren’t drawing from a single source to serve as

downstream feeds to the Cloud, it is easy to see how data changes in key metadata of an organization can hit a wall

of barriers trying to stay synchronized across different silos and with on-premise applications if they exist.

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Introduction

It is no secret that technologies for the Enterprise Performance Management (EPM) suites for most vendors

are becoming Cloud-based. EPM vendors have made strong cases for containing costs by moving from an

ownership model to a subscription-based model. It seems almost a no brainer that for EPM tools like

Planning, Financial Consolidation, and other financial and reporting functions, the subscription model makes sense.

In today’s environment, a subscription model refers to the ability of a user (defined as an organization) to have

access to a dedicated server administered and managed by a third party. The user is no longer responsible for

maintenance, upgrades, or administration of the operating system or any of the software applications that reside

on the server(s). The end user loads his data into the subscribed server and uses the application. Cloud-

based systems are all subscription-based systems, so for the purposes of this discussion, these terms are

interchangeable.

The savings touted for use of a subscription-based model come from eliminating the need for maintaining hardware,

constant software upgrades, infrastructure maintenance, and the costs to have EPM system personnel. There is little

argument that maintaining the infrastructure required for those tools is expensive for customers.

In addition, having a subscription-based model for the tools allows for standardized operating data models that make

the implementation cycle faster and less expensive. This means the tools become useful to the organization in

a shorter period. Those are the benefits; however, the models are more restrictive, and customization is harder

to achieve since the purpose of Cloud-based technology is to allow you to have standardized software that

the subscription provider can easily upgrade when software improvements are made.

Organizations can weigh the benefits and shortcomings of Cloud-based technologies, but they still need to maintain

some type of controls on where data is created, how data is moved to Cloud pods, and when, where, and who

has the responsibility within the organization for maintaining valid data. The need for data governance is not

eradicated when moving to an off-premise platform. In fact, the need becomes more critical because once data finds

its way into the various pods, trying to make corrections becomes cumbersome; since pods don’t communicate

easily with one another, changes must be made in multiple places.

A Data Governance Primer

In this discussion, data governance refers to an organizational philosophy and discipline that leverages

people, processes, and tools to bring orderly modification of an organization’s key master data. The result of such a

program is intended to ensure that correct information is delivered to appropriate groups on a timely and proper

basis. In short, individuals in the organization are given authority to define when, how, and where key

organizational data is changed.

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Data Governance

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Data Governance

Master data for an organization is defined as data used across the organization that defines common pieces of data.

Vendor numbers, customer numbers, and employee numbers are examples of master data. The data tags

and associated metadata (properties) comprise what is required to identify key data to everyone in an

organization. Controlling changes to this data ensures that everyone is using a common reference point when

using any of the common master data.

This is a mini explanation of master data and data governance. A detailed discussion of data governance is a topic

for a separate white paper. For this discussion, it suffices to say that data governance must have all

three components, and software alone does not ensure data governance.

Why the Movement to the Cloud?

It is also apparent that while many EPM functions are moving to Cloud technologies, a lot of organizations

continue to maintain their general ledgers - EBS, PeopleSoft, JD Edwards, etc. - in-house. Organizations have

invested heavily in customizations and infrastructure for their ledgers, and the general sense seems to be that the

current trend is to keep financial systems and data in-house. Since much of an organization’s financial data

required for the EPM suite comes from various ledger modules, it is imperative to create, maintain, and

integrate a standard, uniform metadata repository.

Compelling factors forcing the move to the Cloud are the current trend of EPM functions moving to Cloud

technologies and the tremendous pressure on “C” level functions to follow this trend to reduce costs and

streamline operations to improve the bottom line.

Cloud Movement

Pods give organizations cost effective

access to the latest software tools that

enhance the ability of organizations to

assess their EPM. The chart to the

right from data assembled by Gartner

and Financial Partners International

organizations shows the magnitude of

the increase from 2013 to 2014 and

points to increased acceptance of

Cloud servers in very specific finance

areas by “C” level individuals. Cloud

vendors expect those numbers to

continue to grow as early adapters are

joined by those who move based on

industry trends.

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Data Governance

The increased number of organizations moving to Cloud applications doesn’t necessarily consider the new perils of

moving to the Cloud without understanding the implications. Movement to Cloud-based technologies has its own set

of hidden challenges around data governance and integration. Pod services are siloed environments that solve a

specific set of business functions – planning, consolidation, etc. – but the environments do not easily communicate

or integrate with other pods. The need to ensure that all Cloud solutions are using the same base data remains and

becomes even more essential.

The Cloud technology movement complicates maintaining organizational data governance since it imposes a

requirement to have something that can not only create and maintain a centralized repository of organizational

metadata, but can also interact with Cloud-based pods for all the EPM tools. Organizations must recognize that

their data is as important a business asset as the products and services they provide, and therefore must be treated

with the same respect and care that is required to preserve any legitimate business asset. Today’s largest consumer

transportation firm, Uber, owns no vehicles, and Facebook, the largest owner of popular media, owns no content.

For these and many other organizations recognizing that data is their greatest asset, it forces a change in how

business operates on a day-to-day basis. In the past, companies could tolerate some laxity in data governance and

integration, but the lightning world of e-commerce and mega mergers makes laxity detrimental to success.

Successful organizations must find and use the latest state-of-the-art tools and create bullet proof processes to deal

with the volumes of data collected and stored to allow various groups within the business to function efficiently.

Outdated methods that provide static views are no longer sufficient. Coping in an environment driven by constant

change requires forward thinking and sets the stage for significant challenges. Within the various departments of

any business, the manipulation and integration of data from various operational systems must be timely and

accurate to provide the differing views required for smooth business operations.

Defining the DRM Suite

The DRM suite consists of Data Relationship Management (DRM), Data Relationship Governance (DRG), and Data

Management Analytics (DMA). Each of the tools in the kit is designed to deliver a piece of data governance.

Remembering that no tool by itself is data governance, having the tools and people willing to design and enforce

governance processes and business rules forms the basis for governance.

Pre-Cloud, Oracle DRM was marketed as the tool of choice to (1) manage hierarchies, (2) enable organizations to

enter the data governance arena, (3) provide a centralized repository of master data and associated attributes, and

(4) create mappings that feed downstream applications such as FDMEE.

Post-Cloud, DRM functions do not change. Because DRM is input/output agnostic, each of the Cloud services is

merely another target that can use DRM to source the required structures and associated metadata.

While there are many vendors in the marketplace that tout themselves as a total solution capable of performing the

listed functions, DRM remains a proven product with a strong customer use base and a long history.

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Data Governance

Additionally, Oracle has created an efficient and effective support unit to support its technology, and many of Oracle’s

partners maintain experienced staff with numerous successful implementations. DRM has an earned reputation as a

very versatile tool capable of integrating with several technologies that are both Oracle and non-Oracle. The tool

interacts at a base level regardless of what the input/output targets are. If the client owns other Oracle products,

there are customizations and tools that facilitate those connections and natural integrations.

DRM interacts with Planning, Hyperion Financial Management (HFM), Financial Data Quality Management Enterprise

Edition (FDMEE), Essbase, and E-Business Suite (EBS). It supports custom coding through an open application

program interface (API) and can be configured to receive and output data to flat files or relational data sets. The beauty

of the DRM suite is that it can be installed concurrently or after other Oracle EPM tools. It becomes a centralized

repository for an organization’s metadata and can be either the receiver or sender of that data across the enterprise to

any downstream or upstream system.

Post Cloud: The Silo Creation and Dilemma

The Oracle Enterprise Performance Management (EPM) suite of tools was marketed for a long time as the answer to

removing the silos within an organization. The combination of DRM and EPM created and maintained a centralized

repository of data and metadata that was validated, cleansed, and maintained by the enforcement of rules-based

processes that controlled who, why, when, and where data was changed. At the heart was the notion that well-

maintained and well-governed data improved the quality of organizational data and reporting and ensured that decisions

made across divisions were consistent.

Cloud technologies are uncoupling the strong on-premise ties that naturally occur as a result of having all of the pieces

of the EPM suite in a unified environment. The implication is that in order to maintain the same level of data

consistency across the organization, having an even more stringent data governance methodology is imperative.

Failure to do so will result in siloed processing using disconnected data without any governance. DRM, because it is a

central repository, can facilitate the architected tight coupling required to allow consistency of data across all Cloud

applications.

Equivalence of Business Processes

It is important to understand that not all business functions that are performed by on-premise software have a Cloud

counterpart. This means that to maintain the same level of functional continuity, there needs to be a tight coupling of

on-premise and Cloud offering capability.

Every business process needs to be accounted for, and understanding the input and output requirements for these

processes and their integration with other processes is a necessity. In many cases, this will force the creation of a

tightly controlled hybrid strategy. The key to making sure that the hybrid strategy succeeds is to have the required data

centralized.

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Data Governance

The Cloud’s Diversity Challenge

Movement to Cloud-based EPM technologies has several implications. As previously noted, movement to the

Cloud creates silos since a single pod is focused on a specific business process. The real challenge is to find a

way to synchronize data across pods and the hybrid environments that exist to ensure data consistency so that an

enterprise continues to run smoothly. The degree of data integration required in the siloed environment is very

high.

Additionally, to deploy a business process like planning or financial consolidation in the Cloud, the technology has a

common and static business model to which organizations must conform. This presents somewhat of a

challenge since many organizations live in business climates that demand the ability to quickly ramp up or down.

This means that the static business models employed by Cloud technologies to facilitate rapid deployment become a

significant issue.

To overcome this hurdle, organizations need to look at tools and scenarios that can accommodate the storing and

deployment of rules and models governed and maintained via a governance program that is dynamically

configured to rapidly synchronize data definitions across Cloud environments.

The maintenance of centralized data required across an organization is complicated. Change agents are inherent in

organizations because their divisions and departments have a requirement to use similar data for entirely different

purposes, illustrated in the image below.

Lack of Cloud Application Governance

Many Cloud offerings are relatively new and do not take data governance into account. Vendors like Salesforce and

Anaplan have no current governance solution and have chosen to highlight their functionality and leave the

responsibility for governance to the user.

This is understandable since each pod deals with a sole business function; it would create a very complex

web if every vendor and pod application tried to deal with its own set of governance rules and processes.

This creates the opportunity for a suite such as DRM to fill the void. Most Cloud applications use a common

denominator for integration using either flat files or in some cases support via an open API, and both methods are

natively supported by DRM.

The DRM Business Case

DRM Brings Order

From its inception, DRM has always been considered a strong tool that brings order to any organization

using it. Consider the image below as a pre-DRM scenario:

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Data Governance

Change of key data for an organization has multiple uses. By definition, an organization’s master data is used by

many groups for different purposes. In organizations without any type of master data centralization, the way data is

disseminated and entered into various places is based on requirements. Additionally, there is always a timing issue

since different groups differ in their entry procedures. Because data is manually keyed into different systems, this

creates the opportunity for inconsistency since the different entry points may use different software that may have

different validation rules. A non-governance organization built in differences and inconsistencies results in a

reconciliation process that can be tedious, time consuming, and expensive.

By contrast, consider the image below of an organization that has a governance program like DRM:

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Data Governance

There is a clearly defined business process to enter key master data. It is entered and validated in a central

repository. Data that is related to or dependent on other pieces of master data resides in the central repository and is

not marked or released until it has passed all validation tests. The data is then released simultaneously to all

downstream systems, removing timing and consistency issues. The result is that consistent data is moved into all

systems that subscribe to and use it.

DRM Can Facilitate Movement to the Cloud

Any migration involves data prep and data cleansing. One of the added benefits of using DRM is that it quickly

highlights data inconsistencies and deficiencies. It shows an organization data that violates long-standing business

rules and processes and exposes data inconsistencies in relationships between dimensions.

DRM will serve any organization well that is considering moving to a Cloud-based technology in very specific areas

because it:

1. Organizes everyday changes across the enterprise and puts business rules and processes in place to manage

ongoing changes. It also has the capability to maintain complex business mappings that can be fed to

applications that preprocess and prepare data used by the EPM suite of tools. Finally, it allows maintenance

and creation of alternate trees which permits diverse usage across the organization.

2. Provides a centralized repository that stores hierarchies and associated metadata used by many of the EPM

Cloud applications and stores information in a manner that facilitates transformations for downstream systems.

3. Helps an organization manage risk factors; key master data and associated attributes are entered into a single

controlled environment that is governed by clearly defined business rules and enforced by systemic validations.

Additionally, DRM record-keeping is consistent with Sarbanes-Oxley requirements as well as the internal

requirements of many organizations. It dispenses the same data in a timely fashion to all subscribing systems

and minimizes the opportunity for misstatement.

4. Allows for the peaceful co-existence of on-premise and Cloud technologies that all draw from the same

environment, illustrated in the image below:

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Data Governance

DRM facilitates the move to Cloud technology because organizations that implement this governance tool have

many of the elements used by Cloud applications. Companies can transfer fully governed shared managed

dimensions and all associated metadata via exports into Cloud applications. Any customizations or data

transformations that are mandated by Cloud applications can be performed prior to export using DRM’s derivation

engine with original data elements since it has the capacity to manipulate stored data and export it in any desired

format. In short, the master data and associated attributes are already there and can be easily exported.

Oracle Plans for DRM in the Cloud

Oracle has announced plans to introduce Dimension Management Cloud Service (DMCS), a product that will

perform similar functionality to what currently exists in the full DRM suite. While it is a long-term objective to offer a

full replacement for DRM, it is not one of Oracle’s near term objectives. Initially, the tool will have very specific

functionality focused more on data integration and is not expected to provide governance functionality. Therefore,

DRM will remain a key product to help organizations maintain data governance for not only on-premise applications,

but also for the hybrid environments created as companies move to Cloud technologies.

Conclusion

DRM is a strategic tool for any organization that is considering moving to the Cloud or organizations that have a

hybrid on-premise/Cloud environment. It remains a viable way to maintain data governance needed for

organizations to remain competitive and prevent issues associated with a lack of governance.

DRM has the ability to be the strategic centralized repository that feeds all downstream systems because it treats

Cloud applications as a subscribing system. It is agnostic of environments, sources, and targets, and it still provides

all the functionality and applicability to the same use cases that existed pre-Cloud. This makes DRM an extremely

attractive solution to data governance and integration issues created when moving to the Cloud.

While using DRM without the other prerequisites of people and processes does not give organizations data

governance, it remains an invaluable tool to standardize data used by the backend EPM processes. It allows

organizations to maintain a centralized repository of key master data and associated metadata, and that alone brings

order to many of the EPM processes. DRM can be the organization-wide tool that maintains order, stability of data

quality, and data consistency across the organization now and in the future. It has the capability to grow and evolve

with changing organizational requirements.

It’s flexibility and integration capabilities make DRM the ideal tool to maintain metadata across an organization now

and in the future. It is a tool that grows with an organization and remains the “glue” for the environment whether all

on-premise, all Cloud services, or a hybrid.

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Data Governance

About the Author

Al Moreno

Practice Manager

Al Moreno is a Practice Manager working in the Integration Practice within Edgewater Ranzal. Al is recognized

nationally as an authority in Oracle Enterprise Performance Technology specializing in the Oracle Hyperion Data

Relationship Management (DRM) product suite. He is recognized as a data governance authority and has

authored white papers and articles on establishing data governance in an organization. He is a speaker at Oracle

events focused on the DRM product suite and works as an advisor to the Oracle product team for DRM. He has

been working with the product since it was the Razza Dimension server and has been involved with 60+

implementations over 10 years in the U.S., Europe, and Asia Pacific. He joined Edgewater Ranzal in August, 2016

with 30+ years of consulting experience as well as extensive data warehouse, CRM, and relational architecture

expertise.

Data Governance

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