The explosive growth of data and the value it creates calls on data professionals to level up their programs to build, demonstrate, and maintain trust. The days of fine print, pre-ticked boxes, and data hoarding are gone and strong collaboration from data, privacy, marketing and ethics teams is necessary to design trustworthy data-driven practices.
Join us for a discussion on the latest trends in trusted data and how you can take critical steps to build trust in data practices by:
Embedding privacy by design into data operations
Respecting individual choice and optimizing the ongoing relationship with consumers
Preparing for future data challenges including responsible AI and sustainability
Countdown to Climate Disclosures: ESG Data Management and Mandatory Reporting for Multinational Companies
Authorities around the world have already adopted or are proposing required disclosures related to climate change and corporate sustainability – such as SFDR, CSRD and TCFD. With mandatory disclosures and reporting upon us, corporations must prioritize their management of ESG data – or risk penalties with regulators and shaken confidence from investors. It is critical for multinational companies to have a robust ESG data management framework to not only comply with these numerous ESG and sustainability reporting standards globally, but also to be able to extract value from their ESG data and processes.
Join a panel of experts as they discuss insights gained from ESG customer projects and time to value delivered, including:
Global ESG sustainability reporting developments
Defining your own ESG reporting journey
What the ESG reporting lifecycle looks like
Using frameworks such as DCAM and CDMC to identify and prioritize data management capabilities to meet requirements
How you can harness the power of AI-powered data management technology to get ready for ESG reporting
Innovate Safely in Multicloud with the CDMC Framework for Data Security, Privacy and Governance
Data is becoming the lifeblood of organizations. While it presents great opportunities for developing new products and increasing revenue, it also brings significant obligations to protect sensitive data, honor privacy rights, comply with regulations and manage data risk. As more companies are shifting to hyperscale multi-cloud environments, privacy, security and data governance teams are working hard to mitigate risk and meet compliance requirements. The EDM Council partnered with all the major Cloud Service providers and several leading enterprise organizations to develop the CDMC (Cloud Data Management Capabilities) framework to help organizations tackle these challenges. This panel will explore how to leverage this new framework to build pragmatic solutions for governing data in the cloud.
In this webinar, we will discuss:
Best practices for governing sensitive data in the cloud
Overview of the 14 Key Controls and Automation outlined in the CDMC framework, covering the business and regulatory requirements for managing sensitive data
Tips for operationalizing the CDMC framework
How to migrate data stores to the cloud while mitigating risks
Tales from the Trenches: Lessons Learned From the Industry’s First CDMC Test Case
Moving critical data workloads to the cloud represents a unique opportunity for data-driven organizations to break down silos and grow their data culture. The CDMC (Cloud Data Management Capabilities) and its 14 key controls provide much needed guidance for managing this sensitive data in the cloud. However, the key controls leave much of the implementation details to each organization. Alation and Snowflake teamed up to help close this gap by building the first test case for all 14 key controls and capabilities. KPMG validated the test cases to deliver the industry’s first successful CDMC assessment. In this presentation, we will share how we approached the effort and share examples and details of the implementation.
When you attend this webinar, you will learn:
How to approach closing the gap between CDMC key control and capability requirements and existing capabilities
Common design patterns that support multiple CDMC key controls
How to access and use the Alation test case to accelerate assessment and implementation decisions
Solve Complex Financial Crimes by Leveraging Next-Gen Knowledge Graphs
With the advent of complex financial instruments, fraudsters have found ways to cheat the system by exploiting loopholes and using current technology limitations, to their advantage, which makes it difficult to detect complex web of illegal transactions, corruptions, and connections. The current process of Financial Crime investigation is very manual and time consuming. These complex, undetectable financial crimes need next generation technologies which can perform deep link analysis to identify hidden patterns to detect and prevent crime. There’s also a need to look at crimes holistically across financial crimes domains like AML, KYC, Market Surveillance, etc.
Financial Crime and Compliance Knowledge Graph provides link analysis, algorithms to identify deep hidden linkages, and patterns that fraudsters are using to commit crime. In summary, a Financial Crime and Compliance knowledge graph helps to investigate complex crime and drastically reduces time and cost of investigations.
Our panel of industry experts will discuss:
Why knowledge graphs are different from other traditional technology options?
What are their benefits?
What are the pre-requisites of establishing a Knowledge Graph?
What are the Organizational changes/challenges that you should keep in mind to successfully implement a Graph Investigation platform?
Data Strategies for Accelerating Growth in Financial Services
Join this “Fireside Chat” with Peter Ku, Chief Financial Services Industry Strategist at Informatica, and John Bottega, President of EDM Council, along with their guests Julia Bardmesser, Head of Digital Transformation at Voya Financial, and Israel Abraham, Head of Data Management and Engineering at Mass Mutual, as they share their thoughts and views on data strategies and investments to drive growth, including:
The pandemic’s effect on technology and data related investments
The top data risks impacting industry digital transformation
The impact of cloud modernization on the management and governance of data
The post-pandemic world of the CIO, CDO and CTO across financial services
Key insights for a successful data management and data governance program
Data Governance in Theory vs. Data Governance in Practice
This talk will focus on turning an academic Data Governance framework into a functional, expanding, and maturing Data Governance program. What are the tactical steps an organization can take to turn theory into practice?
When you attend this webinar, you will learn about:
The current state of Data Governance
The tactical “first steps” for Data Governance implementation
Who should participate in start-up Data Governance
How much governance is enough
The role of technology
The best practices which will lead to a successful implementation
What’s the big deal about data observability?
For years, enterprises have run mission-critical data systems with outdated tools that weren’t designed to manage the current exploding supply of data. The problem is only getting worse as massive data volumes, data pipeline complexity, new technologies and hybrid environments conspire to challenge the business value of data systems. This affects everyone in an organization – data teams struggle with operational issues and often fail to meet the increasing demand for real-time data insights, data consumers don’t trust the data they need to make key business decisions, and executives can’t ensure data delivery and pipeline performance meet business requirements.
This session will focus on how, when and where enterprises can apply data observability to:
Successfully architect, operate, and optimize complex data systems at scale
Gain full visibility into data processing, data, and data pipelines
Use ML to automate data identification, quality and management
Manage costs during digital transformation to cloud services
Improve data reliability while reducing operational risk and cost management
A Hive Mind: New NLP techniques to cross-pollinate your cloud and bloom new insights
You’ve meticulously stocked your cloud with data silos rich in internal and external customer information. But to truly bear fruit, the walls of these gardens should be broken down and their contextual signals carried from one to another, with a consistent topic hierarchy.
To take the sting out of these technology and data decisions, this webinar will guide organizations on how to:
Identify opportunities where cross-pollinating data can create exponential value for analytics, BI, ML modeling, search, and more
Evaluate and select a knowledge framework that can produce deep, consistent connections across all data types
Comb through under-utilized data sets and extract new value with innovative Natural Language Processing techniques
Data Security vs. Privacy in a Hybrid Cloud
Data leaders are performing a challenging balancing act. On one hand, data volume is growing at an exponential rate, increasing the need for privacy, security, compliance and risk measures. On the other hand, there is an imperative to accelerate data-driven innovation agendas and share data with external partners to extract new value.
Can privacy and data sharing coexist? It seems necessary to trade off one for the other; prioritize either privacy or data sharing. Data Republic’s approach gives you the power to achieve both.
Join this webinar to explore how secure data innovation and collaboration technology can help you realize the true potential of data assets.
The webinar will explore:
Foundations of the emerging data economy
The perceived data privacy vs innovation tradeoff
Building a scalable and secure data innovation and collaboration capability
Scaling projects with secure technology from Data Republic
Data management considerations for external collaboration
How to get started with on the journey
EDM Association Completes Acquisition of Assets of OMG
The combination of the two organizations creates the world's largest data and standards community.
