Yesterday's breakthrough applications were driven by big data. Tomorrow's innovations will be driven by connected data. Whether your application provides customer analytics, fraud detection, or risk assessment, your users need connected data insights.

Gartner's 2020 report, Top 10 Trends in Data and Analytics leads us to believe that by 2023 graph technologies will facilitate rapid contextualization for decision-making in 30% of organizations worldwide*. Graph data platforms deliver the ability to easily link related data together to create real-time, meaningful, actionable insights and predictions at scale, all while preserving your current technology investment.

In this panel discussion, experts from MANTA, Lucinity, and Capgemini will talk about how graph technology has increased their applications’ competitive edges. You’ll also learn how graphs create:

  • Greater solution value: Surface and employ the relationships that already exist in your data to add value for users in new ways.
  • Differentiation through innovation: Power your analytics and AI/ML forecasting with insights previously undetected at real-time speed.
  • Faster go to market motion: Easily embed graphs with low development effort.

*Gartner. Top 10 Trends in Data and Analytics, Rita Sallam et al., 11 May 2020.

Ernie Ostic
SVP Product, MANTA

Ernie is SVP of Products at MANTA, focusing on solutions for lineage and metadata integration. He has over thirty years of experience in the data integration space, including twenty-plus years at IBM, working in a variety of roles with responsibilities in product management and technical sales support. For most of the past decade, Ernie has been providing guidance in information governance and helping architect custom lineage solutions. Earlier in his career, Ernie was building decision support systems with fourth generation languages and data access middleware. Ernie maintains a blog on open metadata, data lineage and overall metadata management and governance. He is a graduate of Boston College. While not pursuing MANTA initiatives, working on his blog, or spending time with family, Ernie enjoys woodturning and motorcycles.

Justin Bercich
Head of AI, Lucinity

Justin Bercich is the Head of Artificial Intelligence at Lucinity. In his role, Justin is responsible for building and executing Lucinity’s AI strategy and roadmap.

Justin leads the effort to bridge the Human-AI dichotomy, by building trust and synergies between investigators and machines to improve financial crime detection. Justin manages the implementation of production-ready distributed machine learning systems that use cutting-edge explainable AI algorithms and graph technology.

Before joining Lucinity, Justin worked as an Artificial Intelligence specialist at the Financial Conduct Authority, the financial regulatory body in the United Kingdom, for several years.

Justin holds a PhD in Machine Learning and Artificial Intelligence and Bachelor of Commerce (Honors) from the University of Sydney.

Calum Chalmers
Senior Data Scientist, Capgemini

Calum Chalmers is a senior data scientist with Capgemini’s Insights & Data practice in the UK, and is a highly experienced data professional with over 20 years’ experience in the financial, energy and consultancy sectors. In addition, Calum has entrepreneurial experience, previously founding and operating a multi-award winning company in the employee benefits sector. He has an MSc in pure mathematics from the University of Warwick, and a second MSc (with distinction) in Data Science also from the University of Warwick.

Whilst in the financial sector, he has worked for large multi-national financial companies such as Mercer Investment Consulting and Munich Re. It was during his time in the financial sector that Calum studied mathematical finance at Oxford University and studied to become an investments actuary. Calum has extensive statistical and mathematical skills, as well as deep knowledge of machine learning techniques in areas including Natural Language Processing, computer vision/image processing and deep learning.

He has particular interest and expertise in graph theory and its applications, is a member of Capgemini’s global graph practice and also leads Capgemini’s UK Graph Guild, being responsible for the development, adoption and promotion of graph algorithms and graph based solutions.

Dave Packer
Vice President, Product Marketing, Neo4j

Dave has more than 25 years of experience influencing products in the enterprise technology space, primarily focused on information management and governance. As a member of the Neo4j team, Dave leads product, customer and partner marketing, which serve an integral role in product definition, defining the company’s ecosystem and being the voice of the customer for long-term priority setting. Prior to joining Neo4j, Dave held executive positions at TripActions, Druva, Autonomy, Interwoven, and Silicon Graphics.

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