With A-Team Group’s Data Management Summit London just two weeks away on 14 March 2024 at Hilton Canary Wharf, here is a taster of some of the keynotes, panels and practitioner journeys that will be presented by leaders and innovators in the data management field.
The overall theme of the day is the evolution of data strategy to drive business outcomes and speed to market, with sessions covering everything from the role of generative AI (GenAI) in data management to how to deliver a successful data strategy, maximise value from cloud investment, implement data mesh, drive data intelligence, and scale enterprise data quality with AI and ML.
Keynotes
The Summit will open with a practitioner innovation keynote by Niresh Rajah, group chief data officer at Danske Bank. Rajah will set the scene with a CDO’s journey, highlighting key milestones as well as the challenges and opportunities along the way.
Driving greater value from data – Moving on to strategy and the holy grail of driving greater value from data, Jean-Paul Otte, EMEA data strategy lead at Precisely and a former CDO, will give us an inside view on what is resonating at the strategic level that empowers teams to become more data driven. Commenting on the drive to data value, he says: “While data governance is still a hot topic, the market is recognising that data governance, by itself, is not the point. Guiding principles for a more comprehensive, sustainable framework must include active executive sponsorship, hyper-focus on business value, and ambassadors at the business and IT level.”
Data standards and identifiers – Brining standards and identifiers for regulatory reporting to life, Catherine Sutcliffe, regulatory affairs director at the Derivatives Service Bureau (DSB), will provide a preview of how ISO data standards are playing a role in upcoming regulations. She says: “The start of Unique Product Identifier (UPI) reporting in major jurisdictions this year is testament to the importance regulators assign to ISO data standards and identifiers in financial markets. They are integral to the enhancement of data quality through improving accuracy, consistency and facilitating cross-jurisdiction harmonisation.”
Developing data mesh – After the Summit lunch break, Duncan Cooper, chief data officer, asset servicing at Northern Trust, will present a practitioner keynote on data mesh including the data requirements for a data mesh approach, required people, processes and technology, and how to avoid common pitfalls in development.
What’s hot and coming next – Rounding out the day, Helen Sutton, chief revenue officer at Ardoq, will put Ben Clinch, head of information architecture at BT Group, to the test in a keynote fireside chat on data tech futures – what’s hot and coming next for the data technology industry?
Panel discussions
Show me the value – Following Niresh Rajah’s opening keynote, Lorraine Waters, a board advisor and CDO, will moderate what is likely to be a lively C-level user session on how to deliver a successful data strategy – show me the value!
Participants include Elaine Priest, global head of data risk at HSBC; Steve Green, managing director, CDO (EMEA) at SMBC Corporation; Kate Platonova, senior vice president and chief information officer for downstream and renewables at Shell; Ayaz Haji, managing director at BNY Mellon; and Diane Berry, chief data and analytics Officer at Phoenix Group.
The questions will cover the goals of data strategy, metrics that demonstrate value and ROI for data transformation projects, how data transformation is changing the business, and whether the rise of cloud and AI technologies empower organisations or create new dependencies and vulnerabilities.
ROI and value from cloud investment – Heading up a panel on how to get maximum value from cloud investment, Oli Bage, founder and co-chair of the EDM Council Cloud Data Management Capabilities (CDMC) initiative, and head of data and analytics architecture at LSEG, will be asking an expert panel about the key factors for successful cloud deployment and common mistakes to avoid, best practice approaches to visibility, control and optimisation of costs in the cloud, how to minimise data privacy and security risk, and how to evaluate value and ROI.
On this last point, panel member, Chris Brook, co-founder and head of architecture at FINBOURNE Technology, says: “The difficulty in measuring the ROI of moving to the cloud is that it’s never going to be a like-for-like comparison. The cloud can enable capabilities that are impractical to replicate on premise, and the business value of that new functionality is hard to quantify. Modern cloud-based data processing technologies can operate at speeds and scales that were simply unattainable before. The promise of comprehensive, ubiquitous, and timely business information, available to all – not just technologists and analysts – is the real value proposition.”
Data products – Considering best practice approaches to implementing self-service analytics to harness data products, Sally Hinds, managing director of Data Management Consultancy Services, will moderate an expert user panel that will break down the meaning of data products and common use cases, and build up the environment, culture, data ownership, data quality and tech requirements of data products and data pipelines.
Data intelligence – A panel entitled Towards data intelligence – how to embrace metadata driven approaches, semantics, data virtualisation and more to simplify data access and discovery at scale and speed, will be moderated by Naomi Clarke, data innovation and strategy, CDO Advisory, and joined by Lewis Reeder, head of enterprise data governance capabilities at BNY Mellon; Matthew Halliday, data governance practitioner, operations at Schroders; Sam Livingstone, head of data science and data engineering at Jupiter Asset Management; and Tony Seale, knowledge graph engineer at a tier 1 bank.
Questions for the panel include what approaches data managers can take to improve data access and discovery, what is the role of metadata driven approaches in making relevant data sources searchable and accessible for the business, how can tools and techniques such as cloud, data fabric, virtualisation, semantic data, knowledge graphs and data catalogs be used to enable and improve metadata management, and what is the emerging role of ML, AI and GenAI?
How to scale enterprise data quality with AI and ML – The last, but certainly not least, panel of the day will look at how to scale enterprise data quality with AI and ML. Moderated by Mark Davies, Partner at Element 22, it will question whether data profiling combined with AI and ML can help manage data quality, the role of generative AI in data quality, how to use data lineage, visualisation and data observability to identify and fix data quality issues, and how to align AI solutions with data governance and compliance regulations.
Commenting on the potential of AI-based solutions for data quality, panel participant Aisan Baird, vice president, solutions engineering at Precisely, says: “Without trust in data, confidence in AI will rapidly dwindle. The only way to build trust is to proactively make data integrity the cornerstone of your AI driven solutions.”
On the potential of GenAI, panel member Kieran Seaward, head of sales and business development at Datactics, concludes: “In the GenAI era, much of the focus is on the models themselves, such as OpenAI’s GPT-4. Everyone can get their hands on pre-trained models or licensed APIs; what differentiates a good deployment is the data quality.”
Don’t miss A-Team Group’s Data Management Summit London. Join me, Sarah Underwood, editor of Data Management Insight, at the leading financial data management conference for sell-side and buy-side executives in capital markets and hear from data practitioners and innovators who are pushing the boundaries of data to deliver value with flexible but resilient strategies.
View our full agenda and more details here.
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