Name: BCNC's Journey to a Modern Trusted Access Data Platform with Unified Data
Start: 2023-11-30T18:20:00Z
End: 2023-11-30T18:21:02.000Z
Location: BrightTALK
Rating: 0

Reltio's first-of-its-kind, cloud-native platform synthesizes multi-source, complex data into a single source of trusted information. Agile enough to fit any company’s needs, it can flex at will – for accelerated data value creation, and ongoing effectiveness. It’s also fully compliant and secure, so data can be acted upon with confidence. Our diverse set of customers -- from start-ups to large enterprises in more than 140 countries spanning multiple industries -- rely on our award-winning platform to fuel their success. To learn more about Reltio, visit www.reltio.com.

Join us for a moderated panel, with Blue Shield of California, PwC and Reltio, where we will discuss recent observed trends and best practices in data unification and management to reduce costs of healthcare for members. We will dive into how to improve members’ experiences across their interactions with providers and payers by unifying data in near real time.  Our panelists will share their experiences with enabling modern, real-time healthcare organizations with a next-generation data foundation. 
During this webinar you will learn how:
● Blue Shield of California uses its trusted data to drive insights and enhance members’ experiences
● Interoperable, accurate, complete, and timely data can help create value for members'

Data Unification Strategies for Cost Reduction and Enhanced Member Experience

Tired of your rigid, costly legacy master data management system? Join this webinar to explore the modern MDM revolution. You will see a live demo of transformative MDM capabilities that unlock agility, scalability, and cost-effective ways to unify data. You will gain insights into the importance of industry-specific MDM SaaS solutions and the power of ML-driven matching for unparalleled speed and data accuracy.

Unified Data Unleashed – A Closer Look at Modern Master Data Management

Master data management (MDM) is an essential element of any enterprise’s attempt to maintain an authoritative system of records for decision support, data quality management, regulatory compliance, and other purposes. It relies on pipeline processes that validate, combine, match, merge, and enrich similar entities from multiple sources to provide a single authoritative record of each unique entity.

Traditionally, MDM has been managed in data warehouses and other consolidated repositories of structured, transactional data. However, as organizations increasingly distribute their data across multicloud infrastructures, they're evolving their MDM practices to address this new reality. They're also migrating their MDM platforms to address new unstructured and semistructured data sources. In addition, they're aligning their MDM practices to make full use of the data governance they've implemented on their data lakehouses.

Key topics include:

-What are the principal use cases of MDM?
-What business and technical trends are compelling enterprises to evolve their MDM practices toward multicloud and other distributed architectures?
-What challenges do multicloud enterprise data deployments present for enterprise MDM and how should practitioners address them?
-What is the first step that enterprises should take when migrating their MDM practices to run in multicloud environments?

Expert Panel: Changing Practice of MDM in a Multicloud World

About the Webinar
Good data is like good water: best served fresh, and ideally well-filtered. Data Management strategies can produce tremendous procedural improvements and increased profit margins across the board, but only if the data being managed is of high quality. Determining how Data Quality should be engineered provides a useful framework for utilizing Data Quality management effectively in support of business strategy. This, in turn, allows for speedy identification of business problems, delineation between structural and practice-oriented defects in Data Management, and proactive prevention of future issues. Organizations must realize what it means to utilize Data Quality engineering in support of business strategy. This webinar will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor Data Quality. Showing how Data Quality should be engineered provides a useful framework in which to develop an effective approach. This in turn allows organizations to more quickly identify business problems as well as data problems caused by structural issues versus practice-oriented defects and prevent these from re-occurring.

Learning objectives:

-Help you understand foundational Data Quality concepts for improving Data Quality at your organization

-Demonstrate how chronic business challenges for organizations are often rooted in poor Data Quality

-Share case studies illustrating the hallmarks and benefits of Data Quality success

Data-Ed Webinar: Getting Data Quality Right

Master data is a key to digital transformation. All transformative projects require master data and usually many subject areas. Yet the uptake is not where it should be when considering how enterprises could be benefitting with MDM. This is due to several misconceptions.

MDM is crucial to data and business success so in this session, we will identify and dispel those misconceptions.

Common Misconceptions About Master Data Management

The pace of change in digital customer experience is head-spinning; the same applies to technology evolution. From last decade’s multichannel engagements, we have arrived at AI-driven personalization at scale. Life sciences organizations are under constant pressure to modernize their technology architecture to enable a frictionless customer experience and deliver next-generation engagements.  

While they want to tap into AI to offer "next best" experiences, the growing data management complexity makes the task even harder. Building a trusted data foundation is essential to infuse AI-powered insights into real-time business operations.

In this fireside chat webinar, we will discuss the latest data management and cloud enabled solutions that simplify the process and speed time to value.

Who should attend:

CIOs, CDOs, data and analytics leaders in life sciences
Key learning objectives:

The AI use cases and data requirements to enable customized experiences for physicians and patients
Modern data management practices for trusted AI-driven processes

Unleashing AI opportunities with a strong data foundation - AWS & Reltio

Today’s life sciences organizations struggle with having the right patient cohort selection and patient engagement in their clinical trials. This live panel with Moderna, AWS, and Reltio will provide you with recently observed trends and best practices to conduct simplified patient-centered clinical trials based on trusted data foundation and machine learning (ML) practices, along with:

-Moderna’s approach to patient-centric experiences during clinical trials
-How to rapidly dismantle data silos and democratize clinical trials through integrated patient data sets utilizing AWS services
-How Moderna’s cloud-first strategy supports modernization of clinical trials in the era of large language models

Key Learning Objectives:

-How to use the latest data and analytics technologies to simplify the path to trusted insights
-Key considerations and best practices for data harmonization, enrichment, ML to streamline clinical trials and enable omnichannel experiences
-How high-quality data and ML practices can simplify clinical experiences

Simplifying Patient-Centered Clinical Trials with Trusted Data Foundation & ML

Fragmented or poor-quality data is among the biggest barriers to digital transformation and your ability to bring life-saving therapies to market faster. Legacy master data management (MDM) solutions have not delivered.

With modern MDM, you can remove this data barrier across divisions and systems, reduce TCO,  and rapidly deliver trusted, real-time data for your business.  In this webinar, you will learn how Reltio’s cloud-native SaaS MDM unifies and enriches multisource data in real time for key data domains—HCPs, HCOs, patients, products, clinical studies, locations—and enable you to:

Reduce time to value and TCO—and increase IT resource utilization
Improve sales and marketing effectiveness, and offer omnichannel customer experiences to physicians and patients
Accelerate clinical trials and product development to fuel innovation
Simplify compliance with regulations with data privacy, IDMP, the Sunshine Act, and more

Join us and see a live demonstration of how our cloud-native solution with a velocity pack for life sciences reduces implementation time and helps you bring life-changing treatments to market faster.

How To Rapidly Turn Data Silos Into Faster R&D And Commercial Success

It is clear that Data Management best practices exist and so does a useful process for improving existing Data Management practices. The question arises: Since we understand the goal, how does one design a process for Data Management goal achievement? This program describes what must be done at the programmatic level to achieve better data use and a way to implement this as part of your data program. The approach combines DMBoK content and CMMI/DMM processes – permitting organizations with the opportunity to benefit from the best of both. It also permits organizations to understand:

- Their current Data Management practices
- Strengths that should be leveraged
- Remediation opportunities

Data Management Best Practices

Using trusted and timely data is vital to improve operational efficiencies for cost savings and drive better customer experience for revenue growth.  Yet, when business and data leaders need to adopt a modern master data management (MDM) solution to enable transformative initiatives, they have limited information and proof points on its potential business impact to properly prioritize this critical investment. 

We commissioned Forrester Consulting to conduct a Total Economic Impact™ (TEI) study to address this gap and quantify the results our customers have seen by using our cloud-native SaaS MDM platform. The study revealed that a composite Reltio customer achieved a 366% ROI and a total net present value of over $13 million over three years, with a payback within six months. The quantified benefits include better customer targeting with higher quality data and real-time performance, improved first call resolution, team productivity gains, and migration from costly legacy MDM.

In this webinar, featured speaker Forrester Consultant Rachel Ballard will provide a deeper look into the key findings and methodology behind the quantified benefits. We’ll cover:
- The pain points that led businesses to invest in a cloud-native MDM solution
- The process behind the TEI study 
- Deep dive into the methodology and analysis 
- Forrester TEI online calculator to estimate your ROI with Reltio

Forrester TEI Study: How Modern MDM Delivered 366% ROI

Designed to be fast, scalable, flexible, and user-friendly, modern applications are at the center of the innovation and automation that is transforming companies, industries, and society today. At the same time, modern applications, increasingly built with microservices, also come with requirements that traditional data management approaches fall far short of effectively meeting.



From web and mobile backends, to IoT and edge computing, new technologies and strategies are essential to successfully support modern applications in the growing hybrid and multi-cloud world. Don't miss this opportunity to gain a deeper understanding of key solutions and best practices.

Powering Modern Applications: Data Management for Speed and Scale

While collide is perhaps a strong term to use to describe the key area where Data Architecture and Data Governance interact, it does provide motivation to perhaps calm the traffic and avoid further collisions. In order to harmoniously interact, architecture and governance must literally be working from the same diagram (singing from the same sheet of music). The worst time to try to accomplish this is on a short-term decision.  Better still to educate each group to the function of the other and major issues upcoming. A shared Data Literacy exercise can provide a good starting point.

Learning objectives:

-  Gaining a good understanding of both important topics, each’s relationship to the other, and what is required for each to be successful
-  Not to have the first conversation be the important one
-  Coordination is key requiring necessary interdependencies and sequencing
-  Integration challenges can be valued, assisting shared priority development

Where Data Architecture and Data Governance Collide

From data lakes and data warehouses to data mesh and data fabric architectures, the world of analytics continues to evolve to meet the demand for fast, easy, wide-ranging data insights. Right now, nearly 50% of DBTA subscribers are using public cloud services, and many are investing further in staff, skills, and solutions to address key technical challenges. Even today, the amount of time and resources most organizations spend analyzing data pales in comparison to the effort expended in identifying, cleansing, rationalizing, consolidating, and transforming that data. Moreover, while speed is important – 25% of our readers recently ranked timeliness their biggest issue with enterprise data delivery – the overall quality of data is an even bigger concern alongside security and governance.

Join us for a special roundtable webinar to hear expert insights and practical advice – whether you're just starting or already on your cloud journey.

Unlocking the Value of Cloud Data and Analytics

Your enterprise data continuously changes, and so does its quality.  A traditional point-in-time and manual approach to data quality management no longer meets the demands of today’s digitized, 24/7 business.

This webinar features Forrester Research VP, Principal Analyst Noel Yuhanna, Advarra Sr. Director, Enterprise Data Platform Operations, Sajid Sayed, and Reltio VP of Technical Operation, Ansh Kanwar. Together, they will examine the business use cases that drive the need for real-time, trusted data and the data practices that enable real-time operations and better decisions.

Join this interactive, fireside chat webcast and learn:

- The emerging trends in data quality management including continuous, automated, and ML-driven data quality management
- The critical role of data quality management as part of a broader master data management practice
- Recommended data architectures and integration practices to enable continuously curated, high-quality data
- The future of data and analytics solutions for real-time enterprise
- Advarra’s experience with an agile and cost-effective approach to integration

Emerging Data Trends and Best Practices with Forrester and Advarra

In today’s uncertain landscape, organizations need every edge they can get. By breaking down data silos and moving more applications to the cloud, clean, trusted data can fuel companies’ success, better manage security threats and compliance risks while also creating efficiencies and cost savings. Moving data from legacy, on-premises systems to the cloud increases the likelihood of digital transformation success and helps organizations become more competitive.
 
In his presentation, Manish Sood, founder and Chief Technology Officer of Reltio, the industry’s first cloud-native, SaaS data platform, will give an overview of this changing landscape and how some innovative thinkers are beating the odds by leveraging their data as a strategic asset. 
 
In this session, you will learn:
- How organizations break down internal information silos and unlock the power of their data.
- How migrating to cloud-based MDM enhances the customer experience for organizations across industries ranging from insurance to retail to technology.
- How some companies are saving millions of dollars by switching from legacy to modern MDM.

Why Now is the Time to Invest in Your Data

Today’s digital transformation initiatives and cloud-first strategies place great priority on leveraging data assets effectively to deliver business value. Legacy MDM solutions constrain integration to critical business processes by limiting data connectivity, require extensive implementations, and don’t enforce new and different approaches to data management that are required to maximize the advantages of today’s highly distributed technology landscape. Gartner®  tells us that “through 2025, more than 75% of MDM programs will fail to meet business expectations because of a failure to connect MDM value to business value.”* A modern data management approach connects your data to business value by allowing you to activate your data at the quality, scale, flexibility, and speed demanded by modern business practices.

Please join us as Abhishek Shankar - Director and Principal Architect of Data Management at Fresh Gravity, and Guy Vorster - Principal Solution Consultant at Reltio, discuss how modern data management approaches make the practice of MDM faster and easier while enabling you to continuously curate and integrate accurate, timely, and trusted data that delivers business value and meets today’s demands. 

You will leave this session knowing:
- The limitations of legacy solutions and why they are not designed to support today’s business needs.
- How modern MDM capabilities avoid legacy pitfalls and enable cost-effective, agile solutions that drive business goals and digital transformation.
- Real-world approaches and examples of how Fresh Gravity migrates legacy MDM solutions to Reltio and enables modern data management practices that accelerate and simplify business transformation.

*Gartner®, “Magic Quadrant™ for Master Data Management Solutions”, Sally Parker, at al, 6 December 2021.

Migrate to Modern: A Simplified Approach to a Faster and Easier MDM Practice

In today's experience economy, adopting customer centricity and delivering personalized, rich engagements is crucial to attract and retain customers. Data silos across departments and legacy systems cause business operations to rely on outdated and incomplete customer information, hindering seamless customer interactions. Join this webinar to hear real-life examples of how unifying data and improving its quality transform customer experiences by enabling faster service, higher productivity and better operational decisions.  The session will highlight:
-Modern master data management practices for real-time operations
-Quantified business outcomes and improved customer service metrics achieved across industries

How Connected Data Drives Frictionless Customer Experiences

Discover how Blue Cross North Carolina is modernizing its enterprise data ecosystem and building data products for its private data marketplace supporting multiple personas—including those developing AI-ML solutions—in a secure, reusable framework. You will find out how you can tap into the power of ML and the cloud to unify, standardize, and enrich your core business data with greater efficiency, scalability, and agility. The webinar will also highlight how industry-specific prebuilt components can accelerate your time to value to mere weeks and reduce costs, while pretrained ML-based matching supercharges your data team's productivity.

BCNC's Journey to a Modern Trusted Access Data Platform with Unified Data

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BCNC's Journey to a Modern Trusted Access Data Platform with Unified Data

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