Name: How machine learning and cloud adoption helped Mondelez improve sales
Start: 2023-02-24T15:00:00Z
End: 2023-02-24T15:00:49.000Z
Location: BrightTALK
Rating: 4.7

Welcome to the DAMA channel, the Data Management Association providing professional certification (https://www.dama.org/content/certification) & Data Management Body of Knowledge (https://www.dama.org/content/body-knowledge) to members around the world. Our presenters cover topics across the spectrum of Big Data, keeping current on the growing industry. Make sure you check out some of the benefits of membership (https://www.dama.org/content/about-us).

Known as The Data Governance Coach, Nicola Askham helps organisations understand and manage their data better.

For over two decades she has helped organisations reduce costs and inefficiencies. Typically, people turn to her because their data is a mess and they need help unravelling it, or because they realise that new initiatives are failing because of poor quality data.

Description:

Many organisations struggle with Data Governance because they try to do too much, too soon. This practical webinar cuts through the complexity and shows you how to implement Data Governance that actually works.

Drawing on real consulting experience and insights from her new book Effective Data Governance (published by Kogan Page), Nicola will share a proven framework that helps organisations of any size move from overwhelmed to in control.

What attendees will learn:

- Why the 'Big Bang' approach to Data Governance fails (and what to do instead)

- A sustainable four-stage roadmap: Prepare, Design, Implement, and Evolve

- How to prioritise for quick wins and measurable business results

- Six core principles that make Data Governance succeed

- Where AI can help with Data Governance (and where it can't)

- Practical first steps to reduce overwhelm immediately

This session is perfect for Data Governance practitioners, data leaders, and anyone responsible for improving their organisation's data management who wants actionable guidance rather than theoretical frameworks.

How to do Data Governance without getting overwhelmed

As artificial intelligence becomes more deeply embedded in enterprise and public sector operations, organisations are under increasing pressure to ensure responsible and compliant deployment. This webinar explores the essential relationship between AI governance and data governance, and how aligning the two can help build a more resilient and trustworthy foundation for innovation.

We will examine how data governance provides the structure, accountability, and quality controls that AI governance depends on. The session will cover how the two disciplines interact, where they diverge, and how organisations can design governance frameworks that support both data and AI initiatives without duplication or confusion.

This session is intended for data leaders, governance professionals, and AI programme owners who are navigating the complexities of ethical AI, regulatory expectations, and operational readiness. If your organisation is exploring how to scale AI responsibly, this webinar will offer valuable insights into bridging the gap between policy and practice

Lee Biggenden, CEO and Co-founder of Nephos Technologies, brings more than two decades of experience helping enterprise organisations navigate complex transformation journeys. Over the years, he has partnered with some of the world’s largest businesses to modernise the way they manage, govern and protect their data.

Lee’s work focuses on bridging the gap between strategic intent and practical execution, ensuring that governance and compliance are not seen as barriers but as enablers of innovation and growth. He is passionate about helping organisations build trust and unlock business value through better use of their data, sharing real-world insights on how to operationalise data governance at scale in today’s rapidly evolving landscape.

AI Governance Meets Data Governance: Building the Bridge

In large organizations, the integrity of property/address data and asset/infrastructure data is foundational to operational efficiency, regulatory compliance, and customer service excellence. This presentation explores

1. The often-overlooked role of reference data in Master Data Management (MDM)
2. Highlighting how poor governance of location and asset-related reference data can lead to fragmentation, reporting errors, and integration challenges
3. Managing reference data beyond distinct or unique values ensuring that full lists of permissible values are captured, managed and maintained throughout the enterprise through the right processes, workflows and by the right individuals (stewards/owners)
4. Giving Master Data the added value of, not just being a list of key business data for operations & service provision to the customer, but being available to consume for context and perspective in reporting, insights and integration

Takeaways:
Understand the strategic importance of reference data in MDM, especially Customer and Asset Domains.
Understand how to design and govern reference data to support enterprise-wide consistency.

Josiah Kimani is a seasoned Data Expert and certified Profisee Master Data Management (MDM) professional with a career spanning over two decades. His journey in information systems began in 1999, underpinned by a strong foundation in Management of Information Systems in Kenya. After serving in the British armed forces for seven years, Josiah transitioned into the data domain in 2012, where he has since specialized in Data Governance, Reference Data, and Master Data Management. He brings a wealth of experience across industries including telecommunications, healthcare, finance, insurance, oil & gas, utilities, government, retail, gaming, and revenue—working in permanent roles, contract positions, and as a professional services consultant.

Beyond Master Data: Elevating Business Value Through Reference Data Management

The Real State of Data 2025: People, Priorities, and the Rise of AI Pragmatism – A Panel Discussion

This webinar will unpack the real picture of data in 2025, not the hype, but how data teams are actually operating, adapting and prioritising amid economic pressures, AI integration, and cultural shifts.

The Real State of Data 2025: People, Priorities, and the Rise of AI Pragmatism

To achieve success in your data journey, it is crucial to establish effective governance, standardised enterprise data practices, and balance overall goals with the needs of individual business areas.

Governance provides a structured framework for analytics and decision-making, while standardisation enhances efficiency by establishing common practices. Together, these elements promote a culture of transparency and accountability, enabling organisations to adapt to change and drive sustainable growth.



Discover how Elsevier’s MDM approach has supported striking the balance between robust data management practices and trust in data-focused analytics

Learn how these initiatives are positioned at Elsevier to drive sustainable growth and support the ability to adapt to change

Next-Gen Governance: Balancing Data Management and Analytics for Sustainable Growth

Core Competencies:

·       Strategic Leadership: Trusted advisor to senior stakeholders, translating complex data and AI concepts into actionable insights. Known for fostering data literacy, driving cultural change, and championing data as a strategic asset.

·       Information Management: Expert in designing and implementing enterprise-wide data architectures, frameworks, and content lifecycle strategies that enhance discoverability, integrity, and usability across platforms.

·       Data Governance: Skilled in developing governance models that ensure data quality, privacy, and compliance with global standards (GDPR, DORA, ISO 27001, EU AI Act, Consumer Duty, Solvency II etc.) Experienced in establishing data council’s, key working groups, definitions and stewardship programs and embedding governance into business-as-usual operations that drive digital transformation.

·       AI Strategy, Governance and Enablement: Proven ability to craft and execute AI roadmaps and governance frameworks that balance innovation with ethical responsibility. Leads cross-functional initiatives to integrate machine learning, and predictive analytics into core business processes.

Situl is an innovative and strategic data leader with a proven track record in transforming enterprise information landscapes through cutting-edge data governance, intelligent information management, and forward-thinking Data & AI strategy. He is adept at aligning data capabilities with business objectives to drive operational efficiency, regulatory compliance, and competitive advantage. Combines business and technical expertise with executive-level vision to build scalable, ethical, and future-ready data ecosystems.

Impact of AI Governance in the modern enterprise supporting greater innovation

Webinar will cover a practical implementation of Data Quality Governance Model for my client and how it helped them support their overall Data Strategy to improve data maturity curve. It shall cover the challenges faced within their current state and how the implementation of Enterprise Data Quality Management framework supported by Data Ownership Model helped solve these problems. It shall also cover how Central Data Management team can help drive and implement the framework with right DQ Governance operating model covering People, Process, Technology components for various data domains.

Sanjeev Kothari is an accomplished leader in Data & AI Strategy, Data Governance/Management, and AI Governance, with a strong track record of advising C-suite executives and senior stakeholders on data-driven transformation and innovation.  He works as an Associate Director - Data & AI Consulting within Cognizant Worldwide Limited, UK and adept at shaping and executing enterprise-wide Data & AI strategies, Data Governance & Quality Frameworks roll out, building Data Management Capabilities, identifying AI use cases, implementing Responsible AI Framework and driving value creation across diverse industries, including Public Sector, Financial Services, Life Sciences, Manufacturing, Energy and other verticals. A trusted advisor and international Data & AI thought leader, he specialises in building and leading high-performing teams, fostering data-driven cultures, leading regulatory driven transformation programmes and influencing executive decision-making to unlock the full potential of AI and data assets.

Industry Recognition & Awards

Runner up award for Data Story of the Year 2024 from DAMA, UK

CIO 200 UK Master Award for 2024

Top 25 Digital Transformation Leader for 2024 held at Dubai

Implementing an Award Winning Global Data Governance & Quality Framework - postponed until 7 November

Data teams face familiar challenges: improving quality, demonstrating value with limited resources, and managing workflows that demand significant manual effort.

There is potential for AI to be a practical tool to address these issues. In this webinar, Amardeep will share practical examples of how AI can be incorporated into data management and show how it can help data teams scale their impact while keeping delivery trusted and business-focused.

Key Outcomes

    Approaches for using AI to extend what data teams can achieve with existing capacity, with practical examples in data quality, engineering, and insight generation.

    Insights on how workflows and roles are evolving in an AI-enabled environment.

    Approaches to designing delivery around business users, ensuring initiatives deliver measurable value.

    Guidance on embedding trust and governance into AI-enabled workflows.

Amardeep works with organisations to improve data management and quality, leading programmes that deliver trusted data and business insights. His focus is on strengthening data foundations and improving delivery so that data consistently drives business outcomes. More recently, he has incorporated AI models into the end-to-end data lifecycle, using them to improve processes and enable data teams to deliver more value with existing resources. A member of DAMA UK and a CDMP, Amardeep studied Physics at Cambridge and Harvard and brings a practical perspective on how data and AI together can enable better decisions and business growth.

Practical AI for Data Management: Scaling Delivery, Insights, and Business Value

Reference data may not grab headlines, but it underpins every modern data architecture. Without well-managed reference data, reporting becomes inconsistent, integrations break, and data quality issues multiply. In this webinar, we’ll explore the core functionality of Reference Data Management (RDM), why it is a fundamental component of data architecture, and how it ensures consistency, accuracy, and trust across the enterprise. Attendees will gain practical insights into how strong RDM practices can improve data quality, streamline processes, and enable reliable analytics.

Key Takeaways

Recognise the vital role of reference data in modern data architecture.

See how RDM improves data quality and eliminates inconsistencies.

Understand the core functions of RDM — governance, versioning, and stewardship.

Learn how embedding RDM in your strategy enables trusted analytics and reporting.

Palvinder Singh - End-to-end Data & Analytics Consultant with deep expertise in data quality, governance, and insight delivery. I help organisations transform raw data into trusted, actionable intelligence through modern platforms, automation, and advanced analytics.

The Unsung Hero of Data Architecture: Unlocking the Power of Reference Data

Beyond the hype and the marketing AI is changing the way we view data management both from a need for broader scoped, more accurate data sets to opportunities in automation that can accelerate value and reduce risk.

But among the promise there is an abundance of "marketecture", AI being added to everything and a lot of disillusionment in its application. How to determine when it is good for a purpose and not for others? How can we apply critical thinking and common patterns to see when it is likely to work for us and help us avoid moving from data silos to insight silos?

In this engaging fireside chat we cut through the unsubstantiated hype to the modalities that provide real value and controversially we discuss common thought traps (that even Nobel prize winners and leading journalists are falling into) and how to avoid them.

Ben Clinch is a sought after public speaker and thought leader in data and AI. He is a voracious learner, hoovering up books, research papers and meeting with specialists in numerous fields with the sole aim of learning, applying and sharing the knowledge to help others succeed. Ben is a partner at Ortecha and has a passion for helping organisations thrive with their data, built upon practitioner experience having held numerous senior roles in architecture and business in some of the world’s largest financial and telecommunication institutions over his 25 year career. As an active member of the data community, Ben leads an AI Community of Practice and is the lead trainer on several industry wide best practice frameworks.

Fireside Chat with Ben Clinch: How AI is changing the way we think about data management

This talk introduces the Open Data Institute's framework for making datasets truly AI-ready, moving beyond high-level principles to offer actionable guidance. We will explore the essential properties, metadata, and infrastructure required to build a foundation for innovative and trustworthy AI systems.

BCS and DAMA UL are proud to announce the first in a series of collaborative webinars between the two well-known bodies. Thomas Carey-Wilson is a Researcher at the Open Data Institute (ODI) working on the Data-centric AI programme. He focuses on data governance practices throughout the AI data lifecycle, with a keen interest in standards for transformative digital innovations.

BCS News: The BCS Data group is currently featuring  ‘Early Careers’ data professionals. Amongst other aspects this will demonstrate the diverse paths into a career in Data

AI-Ready Data: A Practical Framework for Quality and Trust

Data & Database migration is a major challenge that industry faces across diversified domains e.g. Telecom, Fin-Tech & Government institutions. In Webinar I will talk about Major migration challenges in migrating Production.  Data systems and share my real-life story how I handled different types of migrations (Homogenous, Heterogenous, on-Premises, Cloud migrations).

Key outcomes

    Understand key aspects of this sensitive tasks where business stakes are at its very peak and it is always a pressure-oriented assignments.

    Prepare proactively for any migrations in their environment and have better control over planning, execution, testing and fallback strategies.

Biography: Transformational Data Leader & Cloud Data Architect with over two decades of experience driving enterprise-wide data modernization, compliance, and performance engineering initiatives across global markets. A pioneer in delivering cloud-native data ecosystems.

Data Migration – Real Challenges & Solution

Data Orchard have been researching and measuring data maturity for over a decade.   Their pioneering assessment and benchmarking tools have been used across public, private and not-for-profit sectors to educate, engage, and motivate organisations to improve with data.  Sian will share what they’ve learned so far about organisational data maturity, provide a comparison of sectors and their progress, and highlight case studies of organisations, networks and government approaches to advancing data maturity. There will be plenty of time for Q&A and signposting to useful resources.

Sian is a social entrepreneur passionate about the power of data for making the world a better place socially, economically and environmentally. She’s Co CEO of Data Orchard an award-winning social enterprise that helps organisations get better with data. Since 2015 she’s led their pioneering work on measuring and benchmarking organisational data maturity. More recently she’s created the unique and highly successful Data for leaders training programme.  Sian’s career roots are in digital access and inclusion, digital strategy and impact measurement. Sian has an MSc in Data Science and Analytics and a BSC in ‘Mathematics and Science & Technology Policy’.

Data Maturity, are we there yet? A 5 year comparison of progress across public, private and not-for-profit sectors

In this webinar Daragh will discuss the increasingly irrelevant distinctions between structured and unstructured data and what that means in practice for organisations. He will take delegates through a potted (and irreverent) history tour of how we came to be where we are, will walk through a case study example of what this means in practice, and what it means when we consider it through the DMBOK lens.

Daragh O Brien is founder and managing director of Castlebridge, one of Ireland’s leading consultancies working in data strategy, data governance, and data protection. Since founding Castlebridge in 2009, Daragh and his team have worked with organisations of all sizes across a variety of sectors, including start-ups, SMEs, Non-Profits, Government bodies, EU institutions and other International Organisations. Amongst other publications, Daragh is a co-author of Data Ethics (2nd Edition), published by Kogan Page, lectures in UCD School of Law and the Law Society of Ireland on Data Governance and Data Protection. He is also a member of the Innovation Value Institute in Maynooth University. He is a Fellow of the Irish Computer Society and a Fellow of Information Privacy from the IAPP. Daragh helped develop and deliver the ICS’s pioneering Certificate in Data Protection Practice over a decade ago.

In addition to the day job, volunteer work in various professional organisations, and teaching, Daragh is also doing a Doctorate in Data Governance in the University of Limerick.

Crossing the Streams: The increasingly irrelevant distinction between structured and unstructured data

In a rapidly evolving business landscape, organisations must continuously adapt and refine their strategies if they are going to remain competitive, or even survive. Data is a fundamental enabler of this organisational agility, but only when adaptability has been built directly into the data strategy.

Within this interactive session, drawing on insight from their bestselling book Data Means Business, Jason Foster and Barry Green discuss how adaptability can be baked into the heart of your data strategy to enable organisational responsiveness.

A platform for collaboration and discussion, Jason and Barry will demonstrate why inherently adaptable, data-guided organisations are best equipped to thrive in an ever-changing complex landscape.



Key outcomes:

Learn how to:

Craft a data strategy centered on agility and responsiveness using the Level Up Framework

Build an adaptable data platform

Adapt your strategy to fast-moving internal and external factors

Use your data strategy to enable wider business agility

Why adaptability is mission-critical in a modern data strategy - NOTE Date Change

Driving growth for customers with trusted, rich, complete, curated data, Matt has over 20 years of experience in enterprise software with the world’s leading data management companies and is a qualified marketer within pragmatic product marketing. He is a highly experienced professional in customer information management, enterprise data quality, multidomain master data management and data governance & compliance.

Paari is a seasoned professional with over 12 years of experience in the global retail and consumer packaged goods (CPG) sectors. She specializes in sustainability in supply chain and business operation academically and is experienced in master data management, data governance, and compliance. Throughout her career, Paari has demonstrated a strong commitment to driving customer success by fostering collaboration within business operations. She brings in the understanding of data needs for effective policy implementation and her ability to address data-related challenges for sustainability-focused business growth

Matthew: Driving growth for customers with trusted, rich, complete, curated data, Matt has over 20 years of experience in enterprise software with the world’s leading data management companies and is a qualified marketer within pragmatic product marketing. He is a highly experienced professional in customer information management, enterprise data quality, multidomain master data management and data governance & compliance.

The Value of Master Data Management in Sustainability

With AI continuing to dominate business and leader discussions, those leaders that fail to create a robust data strategy and adopt good data governance risk not achieving lasting ROI and competitive agility.

Increasingly, organisations need a strategic and disciplined approach to acquiring, growing, refining, safeguarding and deploying data to improve the maturity of their enterprise data lifecycle as a perquisite for success, especially with AI.

The more successful leaders around the world are adopting a proactive approach to data management, emphasizing awareness and understanding across the organization. This shift frames data and analytics as a product that drives growth and innovation to manage risk and reduce costs (Gartner, 2023).


Join this 45-minute webinar with speaker Ben Meade, Director of Ringfence and expert in the field of data strategy, governance and management, where we will delve into the key factors that should be on every executive's radar when deciding which data creates the most business value, and how to effectively safeguard and manage this increasingly invaluable asset.

Webinar takeaways

    * A clear understanding of how good data strategy and governance underpins your fundamental value generation activities and can directly improve your performance & outcomes.

    * Insights into what you need to ensure your ‘Information Fitness®’ for the modern, digital world - including AI adoption.

    * Practical tips for ensuring good data governance that link in and align with your wider vision, strategy and risk appetite.

Access to expert knowledge for personalized advice during the Q&A session.

Information Fitness

Data literacy is now a fundamental driver of cultural transformation, decision-making, operational efficiency, and innovation. Without a data-literate workforce, organisations struggle to fully leverage AI, analytics, and emerging technologies.

In this session, we’ll explore:

    The key benefits of Data Literacy – From fostering a confident, data-driven culture to reducing reliance on data teams and accelerating insights. We’ll hear real-world examples from NFU Mutual.

    Overcoming common barriers – Addressing fear of data, leadership buy-in, bridging technical and non-technical gaps, and managing time and resource constraints with scalable, persona-based learning strategies.

    The power of strategic collaboration – Why a dedicated Data Literacy Manager and external partnerships can drive sustained impact, with insights from Farran on stakeholder management and business case development.

    How to get started – Practical steps to assess your current data culture, gain executive buy-in, identify internal champions, and create urgency for investment in data literacy.

For those already on the journey, we’ll discuss how to measure and articulate ROI, ensuring that data literacy is seen as a revenue driver, not an expense. Let’s move beyond tool investments and empower the silent majority because being data-driven is about people, not just technology.

The Business Impact of a Data-Literate Workforce

* Tony Nason, Customer Success Manager, Tamr
* Greg Herrick, Sr Mgr, Analytics Center of Enablement Garage Lead/ MDS Data & Analytics & NA, Mondelez
* Bruno Azizza, Head of Data & Analytics- Google Cloud, Google

How machine learning and cloud adoption helped Mondelez improve sales performance with quality product data. 

Having accurate records on product sales is a must for any organization, especially when you’re snack powerhouse Mondelez International, whose brands include Oreo, Ritz Crackers, Sour Patch Kids and Triscuit.

But data quality issues prevented Mondelez from getting the full picture on how its snacks were selling, and trying to clean up their product data to form trusted records was an extremely manual and time-consuming process.

Mondelez turned to Tamr to curate and clean this data by using human-guided machine learning. They also decided to run Tamr on Google Cloud to leverage the platform’s scalability and flexibility. Mondelez now has accurate product sales records for more informed decisions around initiatives to increase revenue and improve overall performance.

Attend this webinar to learn:
• What business needs led Mondelez to change its approach to master data management
• Why using automation to harmonize product data was a priority
• How trusted product records are being used to drive sales and growth
• The connection between having high quality data and fully utilizing cloud platforms

How machine learning and cloud adoption helped Mondelez improve sales

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How machine learning and cloud adoption helped Mondelez improve sales

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