Accelerate the Transformation
Speed up data processes, Optimize faster for Value
What is BDU?
Big Data Universe Conference is the #1 Big Data HUB for data & IT professionals in Hungary. In the last two years we hosted almost 600 attendees from almost all European countries. Attendees include CEOs and CTO’s of both the world’s fastest growing startups and largest companies, alongside leading investors and many data enthusiast.
Our aim with BDU is to provide the latest trends & insights to data lovers and IT professionals about Big Data management, analytic solutions along with valuable advice and implementable use case examples.
The one day’s agenda will feature presentations from industry luminaries and data experts and provides an outstanding networking opportunity during and after the event.
Big Data Universe Conference 3.0 will focus on practical and technical innovations in the following topics:
Automated chat communication, learning bots
Expanded visualization in 3D
Self driven cars (AI motive)
with BI platforms
Exploring the explosive world of financial technology
Internet of Things & Internet of Everything
``Kubernetes, and cloud native technologies are bringing a significant paradigm shift to infrastructure, big data deployments and applications, and these changes are fast and not incremental. We claim that the existing big data frameworks are all built on out-dated infrastructural components and the proposed changes are too little and too late. We're essentially making the pitch that Kubernetes solves these problems and implies a better separation of concerns between compute, SQL, streaming and the underlying infrastructure, let it be cloud, on-prem or hybrid. Kubernetes has become the de facto standard, as a ````runtime fabric```` purposely designed and built for the cloud and scale and does things the right way - it is an overall game changer and we hope that the big data landscape will benefit from it.
This talk is making the audience familiar with these changes, the drawbacks and benefits of each, and also drive through our journey of implementing a Heroku/Cloud Foundry like PaaS, Pipeline where we move these frameworks from monoliths to microservices.
@ Banzai Cloud
Living the paradigm shift
At Neticle we have designed automated social media text insight discovery methods to let the machine recognize interesting patterns. We have also put focus on how to tell this to our users so we have created a Natural Language Generation (NLG) solution to generate readable multilang insights automatically. I will let you know how we built this solution and how can you create similar.
Text Insight Discovery: From NLP to NLG
Mate has experience in Big Data architectures, data analytics pipelines, operation of infrastructures and growing organisations by focusing on culture spanning more than a decade. Mate also teaches Big Data analytics at Budapest University of Technology and Economics . Speaker and organiser of local and international conferences and meetups.
Data-driven solutions are eating up the Industry. We call it Industry 4.0, the next industrial revolution. We are still in the early stages of this significant transformation, but we already see emerging patterns. Which technologies can come out as the winners of the change coming? What tools and technologies should you invest in? Are Kafka, Spark, AWS and cloud solutions the Holy Grail of IoT? Will AI live up to the hype? What are the low-risk, high return strategies in data analytics? We'll try to answer these questions and look into what the future will bring us in data analytics in the industrial revolution.
Partner and Instructor
Winning strategies and technologies in Industry 4.0 and IoT
The Austrian research project IES-Austria strives to adapt and implement a vendor-neutral and cooperative method to achieve interoperability of ICT-systems in smart energy systems. It is based on an existing method from ICT in healthcare, where interoperability of systems has long been achieved. Integrating the Healthcare Enterprise (IHE) is a global non-profit organisation that engages actors in the health system to achieve interoperability of ICT-systems in healthcare. IHE developed a fair, cooperative and participatory method to engage vendors, manufacturers and users alike. The modular, well-defined process starts with the definition of use cases, followed by cooperatively developing “interoperability profiles” which select, optimise and specify the normalised use of existing technology standards that address the well-defined use cases. These profiles assemble specific “base standards” which together provide complete technical specifications that cover all interoperability issues (e.g. data formats, transport protocols, semantics and security methods).
Senior Project Manager
@ University of Applied Sciences – FH Technikum Wien
Learning from e-Health – Interoperability Process for the Energy System
His mission is to spread data-driven decision making, solving strategy, sales and operation management problems with econometric and data mining models. He is specialized in potential based sales planning and forecasting using geodata, loyalty based customer behavior models, demand curve and price elasticity determination, BI consulting.
Since 2006 Gábor is guest lecturer at the Corvinus University of Budapest, he has been teaching regularly on seminars, local and international conferences. He believes that citizen data scientists can leverage the benefits of analytics, and be the accelerators of integrating data innovations, thus cross-disciplinary knowledge development has to be supported in every education channel.
Managing projects in topics of:
Advanced Analytics, Statistical Analysis, Geoinformation Based Sales Analytics and Forecast, CPM Suites, BI consulting, Business Modeling, Planning and Reporting, Management Control, Management Accounting and Cost Calculation, Performance Improvement.
Head of Advanced Analytics
@ IFUA Horváth & Partners Kft.
data warehouses, data marts, Big Data Framework, dashboarding, visualisation, digital dashboards, mobile BI solutions, advanced analytics,
ETL/ELT reporting (Enterprise Self Service BI - Private Self Service BI - Cloud based reporting - Disclosure management),
Corporate Performance Management (business planning and forecasting, strategic planning and simulation, predictive forecasting, allocating solutions),
Business Process Management (Process modelling, workflow and collaborative solutions & RPA),
Enterprise Project (Portfolio) Management and Project Controlling Solutions.
He has managed projects at more than 50 companies, in different industries.
As a highly professional expert of self service BI, he has held lectures for more than a decade on different Enterprise Analytics topics – at seminars, conferences, university events.
Head of Enterprise Analytics Competence Center
@ IFUA Horváth & Partners Kft.
Accelerate the Transformation with Advanced Analytics in Pricing
Everyone talks about how machine learning will transform business forever and generate massive outcomes. However, it’s surprisingly simple to draw completely wrong conclusions from statistical models, and “correlation does not imply causation” is just the tip of the iceberg. The trend of the democratization of data science further increases the risk for applying models in a wrong way. In this talk, we will discuss capital mistakes as well as small errors that add up to completely ruin the potential positive impact of many data science projects. Attending this talk will hopefully help you to avoid many of those mistakes.
How to Ruin Your Business with Machine Learning & Data Science
The conference is FREE OF CHARGE but attendees must register via Eventbrite.
However VIP tickets are also sold (35.000 HUF) giving you the excellent opportunity to spoil yourself with quality gourmet food, PaaS (Palinka as a Service) and leverage the possibility of excellent networking.