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White Paper

The Self-Learning Enterprise: Staying Competitive in the Digital Era

The Self-Learning Enterprise: Staying Competitive in the Digital Era

Self-Learning Enterprises recognize that data is at the heart of every decision, and more data requires better organization. They organize data collected from various sources into a reliable data foundation. Use of Self-Learning Data Platform with built-in advanced analytics with Machine Learning and Artificial Intelligence promises discovery of new relationships, better insights, and intelligent recommendations to make better business decisions, with a firm focus on improving data and decision quality.

Forrester: Data Technology Pathfinder 2017

Forrester: Data Technology Pathfinder 2017

This complimentary report describes how bottling up analysis and delivering it in a report for business decision-makers is old thinking. Business execs need insights on demand. The data architecture landscape must compress or eliminate the wall between analysis and operations to speed up the business actions and decisions that depend on data. 

Getting IDMP Ready via Modern Product Data Management

Getting IDMP Ready via Modern Product Data Management

IDMP (Identification of Medicinal Products) should not be seen just as a compliance or a pharmacovigilance reporting challenge but as an operational improvement opportunity. It is a strategic project that can transform the entire pharmaceuticals value chain. Any pharmaceuticals company that wants to operate more efficiently in a rapidly changing world needs a way for understanding product data inside and outside of the enterprise.

A Modern Approach to Provider Data Management

A Modern Approach to Provider Data Management


Accurate provider data is critical for operational performance by healthcare providers to realize consumer satisfaction. This paper provides an overview of the challenges healthcare organizations face while managing provider data and recommends an approach to achieving Provider Master Data Management (MDM) that should be considered when establishing a sustainable provider data management process and platform.

Guide to Evolving from Legacy MDM to Modern Data Management

Guide to Evolving from Legacy MDM to Modern Data Management

Having challenges with your current MDM tools? This guide helps you find your way to Modern Data Management. Download the guide to evaluate and plan.

  • Why is it a good time to evolve from legacy Master Data Management (MDM)?
  • What are the elements that align with your key business initiatives?
  • Which new technologies are transforming the data management landscape?
  • Where can you get quick wins to hit your key goals?
  • How can you leverage your current investments and gradually evolve?

Forrester: What You Need to go from Data Rich to Insights Driven

Forrester: What You Need to go from Data Rich to Insights Driven

Forrester’s research shows a strong correlation between higher rates of revenue growth and  two factors: a better customer experience and a concerted effort to use data to be insights driven. Coincidence? Hardly. Our research into how customer-obsessed firms do what they do revealed that becoming insights driven was one of four fundamental shifts in operating principles common to successful organizations. This report shows what being insights driven looks like and lays out the fundamental enablers that enterprise architects must put in place to make that journey.

Modernizing Data Management in Healthcare

Modernizing Data Management in Healthcare

Healthcare continues to undergo significant transformations. With the emergence of Integrated Delivery Networks (IDNs), Accountable Care Organizations (ACOs), and Managed Care Organizations (MCOs), the approach to healthcare is significantly evolving. The focus is on the overall well-being of a patient as opposed to one-time treatments. This patient-centric approach requires a complete understanding of patients, including their demographics, behavior, needs, and preferences. The goal is to improve the overall quality of a patient’s life by building long-term relationships. This paradigm shift in care delivery requires pharma, payers, and providers to collaborate more closely than ever before.

Boosting Omnichannel Sales with Data-driven Marketing

Boosting Omnichannel Sales with Data-driven Marketing

A unique integration of reliable data, relevant insights and recommended actions for all users across the company distinguishes data–driven applications from the ordinary. Marketing benefits through on–demand access to third party data and frees IT from monotonous data loading and management. These applications bring together, and continuously cleanse and relate content, data, and insights across siloed channels. They ensure great experience by tracking customer personalization and adherence to preferences. Ultimately they democratize access to data, allowing for collaboration with e-sales and support through a shared and interconnected view of consumers, relationships, influencers, and omnichannel interactions. 

Accelerating Mergers & Acquisitions with Modern Data Management

Accelerating Mergers & Acquisitions with Modern Data Management

This white paper examines the components of a modern data management platform in depth with special emphasis on how they accelerate pre-merger analysis and post-merger integration. Included is the case study of a multi-billion dollar merger.

How Data-driven Applications will Transform Multichannel and Patient-centric Marketing

How Data-driven Applications will Transform Multichannel and Patient-centric Marketing

A coordinated and compliant multichannel marketing strategy requires finding a way to make sense of a rapidly growing volume of data. Find out how new cloud-based-data-driven applications can transform your marketing efforts and yield the most efficient and productive outcomes.

7 Habits of Data-driven Life Sciences Companies

7 Habits of Data-driven Life Sciences Companies

How do successful life sciences companies develop good data-driven habits? Find out in this eBook which describes 7 habits and scenarios ranging from key opinion/thought leader management, patient centricity, key account management, CIA compliance to mergers & acquisitions, and corporate agility.

Bringing Modern Data-driven Applications to the Enterprise

Bringing Modern Data-driven Applications to the Enterprise

For managers, processes and organizations to be truly data-driven requires going beyond the hype in the press and siloed master data management processes. The success of consumer data-driven applications—such as LinkedIn and Facebook—has shown that frontline users can easily access, improve, analyze, and share their data in a seamless, unified environment. The problem with traditional process-driven applications, such as legacy CRM and ERP systems is that they place the burden of capturing analytical insight, making decisions and taking action on the business user. To correct that problem and offer other benefits, modern enterprise data-driven applications (DDAs) predict and prescribe what to do next with reliable data, relevant insights and recommended actions.

MDM Means Business With Data-driven Apps

MDM Means Business With Data-driven Apps

With many of the legacy MDM solutions due to be refreshed and a plethora of new tools and technologies now available, enterprises are looking for help in the next stage of their journey. Many conversations now focus on extracting timely value from all data types and sources, not just master data. 

Tools and processes are expected to manage all information in near real time and the conversations about evaluating and selecting these tools are now jointly being driven by business and IT representatives with equal passion. This is a fundamental shift in thinking for both IT and business sponsors.