BDA Europe

Big Data Analytics

12 June 2019

Steigenberger Airport Hotel, Frankfurt




Conference Chair’s Opening Address

Vidya Munde-Mueller, Founder | Women in AI Ambassador | {Deutschland}

Building & Delivering your Data and Analytics Strategy

Dr Nedim Dedic, Lead Enterprise Architect, Salzburg AG for Energy, Transport and Telecommunications

One of the most consistent queries which occupy the thoughts of enterprise leaders is ‘’how do I build and develop our data and analytics strategy’’. One of the primary reasons for such concerns is the speed at which data and analytics are changing, which in turn complicates the way businesses seek to utilise its capabilities and presses the need for the development of both workforce upskilling and organisational restructuring.

Our opening address explores how best to build a digital strategy which fully incorporates data and analytics, how incorporation supports a holistic approach, enables transformation and delivers on key business objectives through identification and dissemination of best practice.

Agility Through Enabling Self-Service Analytics

Frank Henze, Vice President of Innovation, Datameer

Are you challenged with accessing your data and the amount of time it takes to prepare and explore data? Join this presentation to discover how to accelerate time to insight by establishing true self-service analytics, without IT losing control over security and governance.

This session will highlight the pitfalls and solutions to extract value from your on premise or cloud data assets in the shortest amount of time. It shares great case studies from customers getting insights on-demand using Datameer and introduces proven architectural concepts which could work for your organisation too.

Bridging the Gap between the Data and the Business World

Vijay Pravin Maharajan, Data Analytics Expert, Siemens

After having graduated from one of the Top-notch Technical universities (Technical University of Munich), and having got professional experiences from huge market-players like Telefonica GmbH, Volkswagen AG and Siemens AG, I now feel that I have the responsibility to share my views on the never-ending story of the vital gap that exists between the Data and the Business world. There is always this talking point on how to bridge the gap, and to bring more values and insights from the data much faster than it is now. Management always expects faster and clear-cut results, without having a clear understanding about data, whereas Data people are not certain about which way to proceed.

•Why is there a gap? – Where are we lacking? – What do we need to do? – How do we do it?
•Decision making – Data / Decision Scientist
•Key of good communication between various floors in an organization
•Social skills that plays a handy role

Adaptive Banking for the Digital Age – It All Starts with the Architecture

Attunity case study presented by Marin Strazanac, Enterprise Architect, Raiffeisenbank Austria d.d. Zagreb

By attending this session, you will gain a deeper understanding of how banks are utilising digital transformation to enhance customer experience. covering tools and techniques such as PostgreSQL, Attunity Replicate, Apache Kafka and Apache Flink; we’ll delve into the new architectures required to implement this at scale using a fast and reliable near real time data synchronization from core banking systems to microservices.

Wait, I'm from marketing. How did I get here?

Marie-Kristin Vuzem, Strategist, WIEN NORD + NOW

The cliché of marketing and technology and the misunderstanding between them is all too often fulfilled and lived in theory and practice.

The content of my talk is primarily concerned with a report on my experiences in training and the industry. As well as the connection between marketing and data science. I would also like to emphasize how important it is that the two topics must be symbiotic in order to achieve the best possible result. Especially with regard to today’s data landscape.

As a career changer, you often have a different perspective. More objectively with the out-of-the-box approach. This has advantages, but you are also often disadvantaged.

• Field report of a newcomer in the field of Marketing and Data Science
• Clearing up prejudices in the area of marketing and IT
• Importance of the interplay of marketing topics and data science based on the example of predictive behavioural targeting

Logical Data Warehouse: The Foundation of Modern Data and Analytics

AUTODESK case study presented by Jörg Meiners, Data Architect, Denodo Technologies

According to a leading analyst firm, the total spend in data and analytics is expected to reach $104 billion in 2019! Companies are investing in data warehouse modernization and data lake projects for descriptive and advanced analytics; however, for the analysis to be holistic, today’s architects weave disparate data streams together, not only from these analytical sources, but also from operational, third party, and streaming data sources. Logical data warehouse is a modern architectural methodology that virtually combines all the data across the enterprise and makes it available to analytical and visualization tools that facilitate timely, insightful, and impactful decisions throughout the enterprise.

Questions to The Panel of Speakers
Morning Networking and Refreshments served in the Exhibition Area
Reflections on use cases of a consolidated cloud-based data warehouse from a business perspective in the media industry

Kristina John, Big Data and Analytics Specialist, Hoy

Digitization has led to a radical change in media consumption over the past decade. Consequently, media investments also underly a fundamental shift. For instance, the medium print lost 54 per cent in advertising turnover over the last ten years, while spending in online advertising increased twentyfold in Switzerland. In addition, the amount and variety of digital channels are increasing.

As a technical start-up of a media agency Hoy is directly coping with these changes. These circumstances led to the decision to build a data warehouse in 2015. Initially, the scope of the project was limited to reporting solutions for customers. But soon, the data warehouse project developed into a more unified framework.

Collecting data in a standardized, systematic way and storing it in a data warehouse provides many benefits: It allows to control for data quality, to implement an alerting and anomaly detection system to react to arising problems in real-time and enables us to generate recommendations based on historical campaign data.

• Learnings since the introductions of a DWH from a business perspective
• Strategic data-driven consultancy of clients and internal consultants
• Acceleration of interactive Real-Time-Dashboards
• Shift from manual work to full Automatization and Automated Data Quality Assurance

Accelerating SQL Analytics on Massive Datasets

A telecom case study presented by Arnon Shimoni, Product Marketing and Solutions Architect, SQream

Join this session to learn how new, GPU-based solutions can provide you with:
• Flexible data exploration with minimal preparation
• Unrestricted access to your organization’s full scope of data
• Previously unobtainable insights, for smarter business decisions

Questions to the Panel of Speakers and Delegates move to the Seminar Rooms
Seminar Sessions
Networking Lunch Served in the Exhibition Area
Conference Chair’s Afternoon Address
Panel Discussion: Women in smart tech

Vidya Munde-Mueller, Founder | Women in AI Ambassador | {Deutschland} 

Mona Szyperski, Co-founder Women Techmakers Frankfurt/ Rhein-Main

Marie-Kristin Vuzem, Strategist, WIEN NORD + NOW:

Aisling Connolly, Cryptography and Privacy Researcher, Information Security, École Normale Supérieure

Kristina John, Big Data and Analytics Specialist, Hoy

Afternoon Networking and Refreshments served in the Exhibition Area
Becoming Information-Driven Rather Than Just Data-Driven

Case studies presented by Hans-Josef Jeanrond, CMO, Sinequa

This presentation draws on a number of concrete customer case studies from several industry sectors, from manufacturing to pharmaceuticals.

It will detail how Sinequa was able to address the need of enterprises to not just manage voluminous sets of data, but make sense of the data, support effective human interaction with such data and improve overall business performance by gaining actionable insights through the effective deployment of AI.

Such increases in efficiency and the insights gained, led to new ideas for business cases and corresponding applications on the Sinequa platform – a virtuous circle.

As the time to market pressures increase, it is vital that enterprises are able to develop new information applications fast in order to support new and changing business cases and shorten the time to ROI.

Examples for business imperatives:

• We must be able to implement compliance rules before a given deadline and respect the time intervals required by the compliance rules, e.g. GDPR
• We must be able to find relevant information fast in order to react to an emergency (equipment failure in a power plant, an aircraft, etc.) or to respect an SLA with a customer
• We must be able to find and share knowledge spread over teams in different geographies, even continents, in order to accelerate R&D projects
• We must be able to rapidly find relevant information from previous RFP responses in order to respond to a new one on time. Ploughing through hundreds of pages per “relevant past RFP” is not an option
• We must be able to rapidly find the right experts to staff a new project

Anti-Money Laundering on Hadoop at a Global Bank

Case study presented by Roland Meinert, Senior Account Executive, Syncsort

An international bank must monitor transactions to detect money laundering for FCA compliance. Machine learning can put patterns, but it needs more than this as large amounts of current, clean data is required. This session reveals the bank´s challenges and requirements and introduces the solution and the benefits Syncsort Trillium provided to the customer meeting stringent anti-money laundering compliance requirements.

Advanced Analytics & Artificial Intelligence – From use cases to an integrative operative approach for the CFO area

Bernd Kälber, Program Manager Advanced Analytics & Artificial Intelligence – Digital@Finance,

The parallel development of Big Data and Artificial Intelligence methods has reached a level of maturity that makes their application relevant in the CFO area of companies. One approach is, for example, to apply machine learning algorithms to certain data areas in such a way that economically relevant hypotheses are tested or planning and forecasting are supported by advanced analytics methods.

We will take a closer look at two specific use cases to understand how this approach can be applied in the CFO area. In order to achieve the whole added value of these concepts, in opposite to several more or less independent use cases, the overall goal for the CFO area must be to arrive at an integrated functional approach for Advanced Analytics & Artificial Intelligence applications.

Questions to the Panel of Speakers
Closing Remarks from the Conference Chair
Conference Closes

Please note:
Whitehall Media reserve the right to change the programme without prior notice.