From Data Science to Data Engineering: the Path to AI Maturity and Performance
Our obsession with powerful AI algorithms has matured to the sober realization that no model – especially a GenAI language model – can perform without clean and trustworthy inputs. Enterprise adopters must therefore modernize their data engineering teams, tools, and techniques to prepare and deliver the necessary data inputs for these endeavors. This session assesses key requirements for data engineering in a GenAI-driven world, then recommends specific steps to meet those requirements and deliver business results with AI.
Kevin Petrie, VP Research | BARC US
Kevin is the VP of Research at BARC US, where he writes and speaks about the intersection of AI, analytics, and data management. For nearly three decades Kevin has deciphered what technology means to practitioners, as an industry analyst, services leader, instructor, marketer, and tech journalist. This includes five years as analyst and Research VP at BARC’s partner Eckerson Group. Kevin also launched and grew a profitable data analytics services team for EMC Pivotal in the Americas and EMEA and ran field training at Attunity/Qlik.
A frequent public speaker and co-author of two books about data management, Kevin is passionate about helping practitioners, founders, and software executives capitalize on emerging technologies. Outside the tech world, Kevin most loves biking, kayaking, and coaching his three boys’ sports teams.
BARC Keynote
Carsten Bange, CEO & Founder | BARC & DATA festival GmbH
Carsten is the founder and managing director of BARC. He is one of the leading experts in the successful implementation of information technology for business intelligence & data management within the framework of the transformation to data-driven companies. As a neutral market observer he has been the coach & strategy consultant for companies of the most varied industries, frequent speaker at conferences, seminars and the author of numerous industry publications and market studies.
BARC Keynote
Shawn Rogers, CEO | BARC US
Shawn has over 28 years of international experience as an industry analyst, thought leader, speaker, author, and instructor on data, business intelligence (BI), analytics, artificial intelligence (AI), machine learning (ML), and cloud technologies. His former analyst roles and executive strategy positions with enterprise software firms give him a unique industry experience.
Data infrastructures from open source to managed services
Current trends include moving from open source systems (DWH’s,ETL jobs, BI tools, MLOps etc) to managed cloud services. Everyone talks about it but what is the reality behind this popularity. At BiTaksi we moved from airflow, postgresql & superset to cloud services. I will talk about the benchmark of cloud platforms(GCP, Azure and AWS) and how we decided to continue with AWS. Also I will mention the challenges we tackled in this modernization and the gains for both data teams and all data users.
Fuad Bayrak, Data Science & Analytics Manager | BiTaksi
As Data Science & Analytics manager at BiTaksi, Fuad leads a team of data analysts, data scientists and data engineers, totaling eight exceptional professionals. He directly reports to the CEO with detailed updates on his team’s achievements, key performance metrics, and the impact of their data-driven initiatives on the overall business objectives.
Artificial Intelligence will be a nightmare without Data Governance
Since the US administration was ordered to appoint Chief Artificial Intelligence Officers, major companies around the world understand that AI cannot be deployed without oversight. In Europe, the AI Act provides a framework, and several ISO standards also exist. But the priority of this framework work is to prepare its data. Yet many companies still believe that AI is magic. Without good quality, compliant and referenced data, it’s impossible to implement effective AI tools. Worse still, this leads to errors, discrimination and hallucinations, which can be costly for the company.
We’ll find out what’s involved in the governance of artificial intelligence, and how Chief Data Officers can add this skill to their roles today.
Philippe Nieuwbourg, Independent Analyst
Philippe Nieuwbourg is an independent analyst specializing in data and artificial intelligence governance. He teaches at several universities, and leads numerous professional training courses.
Panel discussion: Centralization vs. Decentralization
Moderated by: Carsten Bange, CEO & Founder | BARC & DATA festival GmbH
Carsten is the founder and managing director of BARC. He is one of the leading experts in the successful implementation of information technology for business intelligence & data management within the framework of the transformation to data-driven companies. As a neutral market observer he has been the coach & strategy consultant for companies of the most varied industries, frequent speaker at conferences, seminars and the author of numerous industry publications and market studies.
Panel discussion: Costs vs. Benefits
Moderated by: Alex Thamm, CEO | Alexander Thamm GmbH & DATA festival GmbH
Alexander Thamm, is founder, CEO and pioneer in the field of Data and AI. His mission is to generate real added value from data and to restore Germany’s and Europe’s international competitiveness. He is a founding member of the German AI Association, a wanted keynote speaker, and author of numerous publications. In 2012 he founded [at], the first data science consultancy in Germany. Today, the company is one of the leading Data and AI consultancies in the German-speaking region.
*Preliminary schedule, subject to change.
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