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Efficient & Compliant Business with Trusted Reference Data Management (RDM)

Reference data, a subset of master data (lower in volume, variety and volatility), is generally uniform, enterprise-wide and often created by external standardization bodies. Let’s say your customer’s address is a part of a master data record, then the Zip Code and State fields are reference data. It is the kind of data you will find in dropdowns and lookups–restricted values that you can choose from within a field on a form.

The value of reliable reference data cannot be undermined. Due to the nature of IT application development and the reliance upon off-the-shelf application systems, reference data is all too often isolated in silos within many different systems. Inconsistent reference data across multiple systems can cause invalid transactions (state and zip code mismatches), revenue leakages (bad discount codes) and compliance risks (improper tax codes).

As a part of transactional records, reference data is grouped with associated master data and transactional data, and is needed for both operational and analytical master data management enterprise use cases to provide attributes, hierarchies and key performance indicators. Traditional mapping requires human judgment as well as manual synchronization and remediation of reference data. This is neither efficient nor reliable.

To ensure accurate reporting and analytics, proper governance and operational efficiencies, enterprises require a standardization system that makes it easier to define, map, manage and remediate reference data across the organization.

Reference data management is an integral part of Modern Data Management and needs to be a part of your data management strategy. Thinking about reference data in isolation or as an afterthought leads to expensive rework and compliance risks. Since Modern Data Management includes graph technology to establish relations across people, products and places, interesting capabilities result when combined with reference data. With the graph, reference data become pivoting attributes. For example, let’s say physician’s specialty is the reference data, as it needs to map to multiple systems and different physicians. Now speciality_code can be a pivoting attribute, which enables you to drill into a specialty to see the physicians across the organization, and other information relevant to the specialty. The graph makes such relationship management simple.


Today’s data management solutions need a user-friendly solution to define and manage reference data across multiple functional areas, industries and data domains. Whether customer, product or supplier data, Reltio Cloud RDM is a simple, business user-driven application that is adaptable to business needs across any use case required to preserve values and mappings between reference data sets–both in a domain and across domains.

Unlike other legacy MDM tools, that charge separately for basic RDM capabilities, Reltio Cloud Modern Data Management Platform as a Service includes core RDM functionality built-in. Being built-in makes it much simpler to ensure that there is consistent reference data for all downstream operational applications. By managing complex mappings among customer, partner, product and supplier data domains, and managing their interrelationships, enterprises will improve data quality and reduce compliance risk.



Governance of reference data is vital–manual or custom RDM often lacks change management, audit controls and granular security and permissions. Due to the complexity in managing and governing reference data, an RDM solution should include a seamless, intuitive user interface to manage lookups, and ensure data consistency across systems with version control, security and access controls. Reltio Cloud’s RDM facilitates remediation and improvement of reference data quality along with mapping to localized data, which helps with global harmonization. Built-in workflow capabilities, such reviews, approvals, history and audit trails help make structural changes to reference data with complete governance.


RDM data are often managed by business users who want to maintain, manage, standardize and remediate reference data at their fingertips. They need complete visibility into the “Crosswalks” for understanding data change impact. Collaborative curation of information through fine-grained workflow and governance allows cross-functional teams get the most accurate information real-time. Teams should be able to flexibly deliver information to downstream applications or provide access through embedded widgets within operational applications.


In many cases, organizations purchase or subscribe to third-party data sources for verified reference data. Lines of business want an easy way to connect to third-party reference data sources to enrich the existing data. Data as a Service within a modern data management platform lets you connect to such data sources, and merge the data with other master data for your data-driven applications.


A Modern Data Management platform lets you connect to existing MDM, operational applications and third-party data sources for real-time integration. User-friendly interfaces with import and export capability help map reference data sources quickly, and eliminate the burden of managing reference data sets. Reference data from multiple source systems require no transcoding, translation, custom code or IT involvement. Configuration, Lookup and Transcode REST APIs are available to manage reference data through integrations. A multi-tenant cloud platform ensures ease of provisioning and zero downtime upgrades. Deployed in the cloud, you will be delivering value faster than ever possible without the overhead of managing the infrastructure for this highly critical and available data.

Mona Rakibe is a Director of Platform Product Management at Reltio. She’s an expert in data management technologies with a specialty in content management and BPM, having worked for companies such as EMC, Oracle and BEA Systems.

Get ‘IDMP Ready’ with Modern Data Management

There is no better time than now for pharma & medical device companies to modernize their product information management and comply with IDMP (Identification of Medicinal Products). Non-compliance might result not only in hefty penalties (as high as 5% of annual EU gross revenue) but also in poor operational efficiencies. Experts advise to kick-off the IDMP initiative now and reconfigure the data model later when the final guidelines are published by EMA (European Medicines Agency), FDA (Food & Drug Administration) or other similar regulatory body.

IDMP is a set of five ISO norms which has been developed in response to a world-wide demand for internationally harmonized specifications for medicinal products. Following a phased implementation process, pharma & medical device companies will be required to submit data on medicines and medical devices to EMA in accordance with these formats and terminologies. The implementation of the IDMP standards will help achieve operational savings for these companies as well as improve the health and safety of the human population.

Product information in pharma & medical device companies is distributed across several departments or lines of business in a myriad of different systems, authored in different formats, in multiple languages, and different terminologies. Harmonizing this data within a single organization itself is a big challenge, but doing so across the continents and coming up with common standards is a daunting task. It is for these reasons, the timelines for implementations of IDMP standards have been changed a few times. This valuable grace period should be utilized by these organizations in planning and preparing for this ambitious, enterprise-wide initiative.

As per the EMA, the underlying challenge of IDMP is fundamentally a Master Data one. EMA’s approach to implementing the ISO IDMP standards is based on the four domains of master data in pharmaceutical regulatory processes: substance, product, organization and referential (SPOR) data. Pharma & medical device companies that would be regulated as per the IDMP standards by the EMA, should be right now actively getting a handle around where is their product data scattered within their enterprise, and how they would manage it scientifically.

A Modern Data Management Platform allows you to create a strong underlying master data foundation for IDMP objects in the cloud as well as derive actionable insights from various data domains, their relationships, and the interactions among them by leveraging graph technology. It not only creates the reliable product data foundation but also offers flexible product hierarchies by markets, brands, segments and geographies that can be categorized, organized and analyzed from multiple perspectives.

It is extremely easy to write metadata based definitions of IDMP objects in an agile, real-time configurable data management platform. Not only can you start with the definitions of these objects as per the evolving IDMP standards, you can also extend these definitions over time based upon your varied business needs. You can create other objects over and above the IDMP objects, define relationships among themselves, and capture transactional data that will eventually provide valuable insights. Reference Data Management is yet another underlying capability of a Modern Data Management Platform that helps master reference data from multiple systems. In the world of IDMP, the reference data can be sourced from different systems. As an example, Global Substance Registration System (G-SRS) is one of the major source systems that implements and supports the ISO-11238 substance types and controlled vocabularies (CVs).

Last but not least, a cloud-based Modern Data Management Platform requires no on-premises installation, hardware or maintenance. Instead of buying servers, installing and patching software, and constantly wrestling with how to handle the relentless growth and diversity of data, your IT teams can focus on delivering relevant, operational intelligence to business users. Such platform is deployable in a fraction of the time and cost compared to the traditional MDM solutions, providing significantly faster time to value. Also, it provides fine-grained, attribute-level, visibility of who searched for, who looked at, and who modified what data, in logs that can be tracked and monitored for security and compliance.

Business leaders who can adopt a modern data management philosophy, program management teams that can help drive the project, and technology partners who can help implement specialty technologies, would need to come together to make full, organization-wide IDMP compliance a reality. Using a next generation data management platform for your IDMP implementation will not only reduce the time to compliance in a cost-effective manner, but it will empower your organization to create a futuristic data platform that will stay current. In addition, it will help you build new capabilities such as providing transparency to your consumers, facilitating acquisition of other products or companies, and identifying emerging product safety risks apart from meeting regulatory requirements and delivering cost savings.

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CIO & CDOs: How Does Brexit Impact Your Data Management Strategy?

By now I’m sure you’ve had more than your fill of Brexit analysis, memes, and even a tie-in to the England National team’s exit from Euro 2016 tournament.

It’s been well documented that the vote doesn’t mean that the UK is leaving the EU tomorrow. Some speculate it could take until 2020 before any action is taken. But companies across the globe do need to plan for that eventuality, and one key area is ensuring that they remain agile with their data management, and privacy protection strategies.

A major analyst firm wasted no time in issuing a research note titled “CIOs Must Act to Prepare for Changes Triggered by Brexit”. The note covered a wide variety of areas from cost optimization, people and talent through to governance and operating model changes.

Businesses in Europe will see a stall in IT spending as a result of the U.K. vote to leave the European Union. CIOs need to provide frequent, open communication and create a task force to prepare for the changes.

In the area of data management, many have been quick to point out that the General Data Protection Regulation (GDPR) passed by the EU late 2015 already has strong requirements as it pertains to:

  • Accountability of businesses to demonstrate compliance including privacy impact assessments, key in healthcare data, in which the risks to an individual during the use of that data must be detailed

  • Data erasure aka “the right to be forgotten”, meaning removing any historical activities made by individuals captured as part of their digital activities

  • Profiling which relates to the need to obtain permission from individuals before any of their profile data is used to evaluate their behavior. Credit scores are an example of such profiling

  • Data breach notifications that dictate the minimum acceptable time periods upon which individuals or organizations must be notified when profiles containing their data is compromised

If the UK is no longer part of the EU, this may seemingly free UK companies from having to conform. However the GDPR is likely to be enacted in 2018, before the UK would leave in say 2020. And the UK and other companies doing business in the EU would still have to conform.

Additionally the GDPR actually determines data security and privacy policies for members of another group known as the European Economic Area (EEA). The analyst firm further points out

Brexit vote applies to the U.K. leaving the EU, it does not address the question of whether the U.K. will remain within the EEA (for example, Iceland, Norway and Liechtenstein are members of the EEA, but not the EU). Consequently, CIOs with data located in the U.K. will still need to continue with plans to comply with the new regulation until more information is provided on the U.K.’s future position in the EEA.

An Information Week article “Brexit: Will Cloud Vendors Hear London Calling?” speculates how Brexit might impact the investments being made in data centers by giants such as Amazon and Microsoft.

Amazon Web Services and Microsoft are in the process of adding to their cloud facilities in the UK. IBM has already done so. All were trying to establish cloud centers close to what has become the emerging financial center of the EU.

While an article in the Financial times takes another perspective suggesting that

Regional Cloud service providers would not be able to reach the scale needed to compete with global rivals, instead forcing them to rely on local data centers run by Amazon Web Services and Microsoft, which already operate at an order of magnitude, this person said. “What we’re moving towards is a duopoly of AWS and Microsoft.”

As we’ve seen by global reaction, and the gyrations in the stock market, the uncertainty is overwhelming.

Reltio’s CEO Manish Sood in an interview with ComputerWeekly pointed out that

Data privacy and protection laws are becoming increasingly stringent, and are slowly catching up to the wealth of data being captured and used in the digital age.

Organizations who naturally see data as an asset for digital transformation, improved customer experience, and personalized targeting, have multiple hurdles to go through to conform to not just new regulations like GDPR, or even the EU-US privacy shield. The key for any organization wanting to do business globally is to use data management platforms and technologies that are agile enough to comply with all of these laws today, and as they evolve. Only then can they maintain their competitive advantage using data, and prevent their data turning into a compliance liability.

So maybe Brexit is just another wake up call for your company’s data management strategy.