Data Science Economy: Dawn of AI
4 keynotes / 22 talks / 30+ speakers
Conference Schedule!

16. – 17.05. 2019, @KRAŠ Auditorium, Zagreb, Croatia

RLS: Real Life Use Cases and Stories: Lectures describing details about business and technical perspective of concrete real-life use cases based on relevant subject areas (Data Ingestion, Real Time Processing, Machine Learning, Predictive Analytics, Natural Language Processing,  Data Visualization, Artificial Intelligence etc…

CAL: Concepts and Learnings: Lectures related to general advices, experiences and recommendations about logical architecture, technologies, trends, tools, concepts, project organisation, data governance, data protection and beyond.

WNX: What is Next, Trends and Future Development: anything emerging, looking to be disruptive in the field of data science and applications of data science. Looking at the future, showcasing the things that will keep us awake in the months to come.


Day 1, 16.05. Thursday

Conference Day

Here, you attend the predefined sessions and learn from case studies, presented by great speakers.

Conference Registration

08:30 – 09:00
Early bird catches the worm and get’s on time to hear the opening keynote. 🙂

Welcome to the Conference!

09:00 – 09:10
Welcome to the Data Science Economy Conference!

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Laura Bermudez, Carta, Palo Alto, US

Keynote: Disruptive data in Silicon Valley – How Carta is Leveraging Data

09:10 – 09:50 IN ENGLISH
Data is disrupting the world. Companies everywhere are looking at their businesses, products, and customers in entirely new ways through the lens of data. Listen to how Carta, one of the fastest growing tech companies in Silicon Valley, is reinventing the FinTech landscape and changing how ownership is managed through its use of data.

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Mario Meir-Huber, A1 Austria & Maja Copak Smolčić, A1 Croatia

Keynote: Data Science experience: from group strategy to local execution

09:50 – 10:30 IN ENGLISH
In this session, Maja and Mario will talk about how the collaboration on Data Science and AI works in large enterprises. They will give an overview on how to bring general priorities, actions and obstacles from the Group to a local country execution. Main focus will be on the projects and best practices shared between the Group and A1 Croatia.


Coffee Break

10:30 – 11:00

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Zdenek Demeter, Bisnode, Czech Republic

Keynote: Data science – a cornerstone for future business growth in any industry

11:00 – 11:30 IN ENGLISH
Data and analytics capabilities play a key role in most of current business processes. Regardless industry it helps sales guys spot a new sales potentials, increase marketing campaigns results, assess customers value and risk profiles or taking care for a great customers experience on most touchpoints of these days.
Zdenek will present practical examples how analytics enables business growth, how external big data sources can improve customer insights or how to setup a sustainable analytical team to do it right.

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Marko Rakar

Keynote: What are your digital traces telling about you?

11:30 – 12:00
We are surrounded by sensors. This sensors are collecting data about us and our environment. With wide avaliablity of sensory data, some creative thinking and use of machine learning and artificial intelligence alghoritms we can start discovering stories which are far beyond original intention of sensors which collected the data. This data can quite often be used to draw completely unexpected and unintended conclusions about us, our behaviour and habbits. They invade our privacy in ways previously unthinkable and to most people completely uncomprihensible.

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DSE 2019

Talk show: Data business

12:00 – 13:00
We will hear from the first hand what stakeholders from Telecom, Finance and Tourism think about Data Science in their field and what we can expect in the future of Data in Croatian business. As this is talk show, expect a fun and relax approach to the subject. Petar Štefanić, experienced journalist and TV host on N1 will make sure that talk goes smoothly and interesting.

Guests:
– Monika Majstorović, Marketing director – Enterprise, A1 Hrvatska
– Dejan Donev, Head of Digital Transformation Team, Erste Bank
– Marko Lukičić, Management Board Member, Jadranka d.d.


Lunch

13:00 – 14:00

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Anđela Velimirović & Jasmina Glišović, Things Solver, Serbia

RLS1 How can data science help retailers: store expansion case (Gomex Serbia)

14:00 – 14:30 | Academy Room A | IN ENGLISH
In times when data science and advanced analytics are almost ubiquitous in terms of various industry applications, we decided to help a fast growing retail chain to make better decisions on their way to become market leader. With various static and dynamic data parameters at our database, we aimed to optimize current business operations and develop decision making support system for store expansion.
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Tomislav Tipurić, Nephos

CAL1 NoSQL – the brave new world of operational dana

14:00 – 14:30 | Academy Room B
Data is the most important thing in the world today. The number of data technologies literally exploded in the past decade. There are relational databases, non-relational databases, various analytical tools, numerous data warehousing solutions, data lakes, and various stream analytics technologies. Generally speaking, all data storage technologies can be divided depending on the type of data they manage, which can be operational)… (for more info press speaker photo)
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Martin Frešer, Business Intelligence Developer, Adacta

WNX1 How is AI transforming Hospitality

14:00 – 14:30 | Academy Room C IN ENGLISH
Discovering hidden patterns in customer behaviour has shown challenging yet very valuable for different fields, such as retail, entertainment industry, etc. Progress in AI field, both, in terms of state-of-the-art algorithms and increased computational power has enabled us to unveil patterns and use the output to make data-driven decisions. Nowadays everyone can book… (for more info press speaker photo)

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Mikheil Nadareishvili, TBC Bank, Georgia

RLS2 Developing Mature Data Science Function

14:30 – 15:00 | Academy Room A IN ENGLISH
Data Science has reached a point of maturity in large organizations. Having proven its value on fascinating niche use cases, it is now on every executive’s mind and ready to radically transform business-as-usual processes. But in order to pull off the transformation, the organization and method of delivery of analytics must change first. Data scientists should transform from isolated “unicorns” to being part of… (for more info press speaker photo)
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Albert Ćosić, Data Science Team Lead, Neos, Croata

CAL2 Key ingredients of successful data science project?

14:30 – 15:00 | Academy Room B
Although we fully support the predictions advocated by most consulting firms that companies that do not invest in data science-based projects do not have a bright future – we are witnessing a large number of unsuccessful projects or ones with questionable profitability and expected results (according to recent Gartner research – big data projects failure rate is high as 60 and some argue that it even goes up to 85 percent).
According to data scientist practitioners and their leads there are… (for more info press speaker photo)

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Tomislav Hlupić, Poslovna inteligencija

WNX2 Building a recommendation system for IPTV on a fast streaming architecture

14:30 – 15:00 | Academy Room C
The talk will be a mixture between a description of fast streaming architecture on which the system was built on and the IPTV recommender system that Poslovna Inteligencija has developed. The overview of the topic will be given in the introduction, following by a description of content delivery services and the data produced by them and how it is used in the customer experience. (for more info press speaker photo)

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Niko Draganić, Head of Data Science, KOIOS

RLS3 EU Parliament: What does the data say?

15:00 – 15:30 | Academy Room A
Presentation will be showing a brief overview of the EP structure and data transparency and availability. What are our expectations? What are the limitations? How well does the data fit our needs? Are we asking the right questions?
We then continue by comparing member states and political groups by MEP activity. We introduce measurements such as success index on the group / state level and… (for more info press speaker photo)
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Ivan Čeliković, Syntio

CAL3 You have lots of great ideas on how to use Data Science but you are unsure on how to start?

15:00 – 15:30 | Academy Room B
How to structure your teams? How to setup an enterprise environment? Which tools to use? How much time and other resources to spend on a certain idea before cutting it loose? These are some of questions we will try to answer in a reflection on a 2+ years ongoing project focused on a Big Data Platform in retail industries. (for more info press speaker photo)
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Imre Szucs, Advisor in AI/DS, Hungary

WNX3 Data Analytics as a Service – cross industry collaboration

15:00 – 15:30 | Academy Room C IN ENGLISH
On markets where the competition is strong and new entrant’s disruption is a risk this is a must to do business from one of the most important asset: the DATA. How can we monetize our data and analytical capabilities and how can other industries benefit from this collaboration while respecting data privacy?
The presentation will focus on the practical challenges of Data Analytics as a Service.



Coffee Break

15:30 – 16:00

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Mario Jurić, Head of Big Bata & Data Science, Megatrend

RLS4 How to start and scale with Data Science

16:00 – 16:30 | Academy Room A
This presentation is intended for all of you who are thinking about starting with the Data Science in your company or you’ve already doing it and want to scale it. You will be able to learn how to face some of the biggest challenges in Data Science projects:
– Starting with your first project
– Increasing productivity and enabling collaboration between data scientists, analysts, developers and subject matter experts
– Accelerating machine learning model development and time needed form idea to production ready application.
– Deploying machine learning models into production and really start to use it
– Choosing right tools that can help on this journey
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Tomislav Mališ, BI Developer, PBI Expert

CAL4 Managing sales operations using Microsoft Power BI (data insight for masses)

16:00 – 16:30 | Academy Room B
Showcase of real-life direct sales operation where performance tracking and data insight is done using Microsoft Power BI. Data that will be used is both external and internal. We’ll show how to easily overview actual performance, actual vs planned, actual vs previous period performance, how to use Power BI data insights feature that is built on a growing set of… (for more info press speaker photo)
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Vladimir Marković, Intesa, Srbija

WNX4 Can unsupervised machine learning help in fraud detection?

16:00 – 16:30 | Academy Room C
Fraud is a „profitable“ business and it is increasing every year. Traditional techniques of fraud detection are complex, time-consuming and request domain knowledge like business practice, finance, economics, low etc.
Well-designed applications have readable application logs, and well-described business processes in terms of data. Usually, we use all available in the development… (for more info press speaker photo)

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Saša Radovanović, Qony, Serbia

RLS5 Translate Data Science into company needs. Don’t let it stay Science.

16:30 – 17:00 | Academy Room A
Data Science is still fairly kept on the level of multinational corporations & universities. Multinational corporations are exploring new machine learning algorithms, using deep & re-inforced learning, mainly for protection, security & cost savings. Universities are, on the other side, teaching data scientists to get as deep as possible into scientific part of data manipulation, mathematical equation and probabilities, statistics… (for more info press speaker photo)
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Renee Ahel, ML practitioner and aficionado

CAL5 Lessons learned in Data Science

16:30 – 17:00 | Academy Room B
What are the key factors causing the success or failure of a Data Science project? Presenter will guide you through them all, and illustrate with examples from his own experience. Whether you are an experienced data scientist, novice or a manager contemplating on how to start with Data Science in your company, this presentation is for you.
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Ben Dean, Iconoclast Tech LLC, Australia

WNX5 Using Data Science to fill the gaps in cyber risk data

16:30 – 17:00 | Academy Room C IN ENGLISH
Empirical data on cyber risks, like data breaches or ransomware, are by their nature incomplete, censored and patchy. In particular, to quote Donald Rumsfeld, there’s many “unknown-unknowns“ that have to be included in risk models. This talk will provide a ‘from the trenches’ perspective on what tools a data scientist can use to… (for more info press speaker photo)

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Enkelejd Zotaj, Executive director IT, Raiffeisen Bank, Croatia

RLS 6 Data a foe or friend: The case for leapfrogging, from legacy to streaming architecture

17:00 – 17:30 | Academy Room A IN ENGLISH
Banks are plagued by legacy, systems implemented in different ages, each bringing its own footprint. Data inconsistencies across channels, served differently from proprietary systems create sluggish customer experience, inconsistency and translate in friction to customers.
We at RBA believe that transiting to a streaming architecture, growing in experience and confidence across all our agile teams to leverage data, understand and utilizing data will give us an edge.
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Davorin Kopič, Zemanta, Slovenia

CAL 6 Building an effective Data Science team

17:00 – 17:30 | Academy Room B IN ENGLISH
If your organisation is anything like ours, then Data Science teams have huge and direct impact on the business and bottom-line figures. So you have probably been asking yourself how to build an effective Data Science team. In our team, we are developing machine learning algorithms that are powering hundreds of thousands… (for more info press speaker photo)
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Mislav Malenica, CEO, Vingd

WNX6 Want superhuman diagnostic capabilities? Look what I have for you!

17:00 – 17:30 | Academy Room C
How we copied the brain of one of the world’s top diagnosticians and made it available to 10M people around the world for free. We’ll demo the system, show the architecture and explain how we built ML models that are good enough to pass strict medical evaluation in a situation where there is a clear lack of relevant training datasets.


End of Day 1

17:30

Day 2, 17.05. Friday

Workshop Day

Over here, you participate in one or more great workshops delivered by individual speakers

Workshop Registration (Kind-Of)

08:30 – 8:50 Kraš Auditorium
Given that you already registered a day before, no big deal. If someone else is attending on your name, no problem – just let us know!

Welcome to the Workshops!

08:50 – 9:00
Welcome to the Data Science Economy Workshops!

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Marko Štajcer, Director of Innovation & Development, Poslovna Inteligencija

WKS1 Machine Learning for the Elastic stack

09:00 – 10:30 | Academy Room A
Complex, fast-moving datasets make it nearly impossible to spot infrastructure problems, intruders, or business issues as they happen using rules or humans looking at dashboards. Elastic machine learning features automatically model the behavior of your Elasticsearch data — trends, periodicity, and more — in real time to identify issues faster, streamline root cause analysis, and reduce false positives… (for more info press speaker photo)

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Marko Dobrinić, Data Scientist, Megatrend

WKS2 Developing real world applications with computer vision

09:00 – 10:30 | Academy Room B
INFO FOR PARTICIPANTS – Bring your laptop to this workshop!
IBM PowerAI Vision is a tool that enables quick labeling of data, as well as development and deployment of deep learning models. It includes the most popular deep learning frameworks and their dependencies, and it is built for easy and rapid deployment and increased team productivity. By combining PowerAI Vision software with accelerated IBM® Power Systems™, enterprises can rapidly deploy a fully optimized and supported platform with blazing performance. (for more info press speaker photo)

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Vladimir Marković, IT Auditor, Banca Intesa Beograd, Serbia & Grozdana Marić, SAS

WKS 3 How unsupervised machine learning help in fraud detection?

09:00 – 10:30 | Academy Room C
Introduction to internal fraud – some cases
SAS Visual Investigator demo
How to use advanced analytics in reducing sample of suspicious
About anomalies
o Assumptions – choice of the method
o Some techniques in detecting anomalies



Coffee Break

10:30 – 11:00

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Kristina Reicher, Business Intelligence Consultant, Koios Consulting

WKS4 Scraping and analysis of the EU Parliament open data

11:00 – 12:30 | Academy Room A
In this workshop we will show the Python packages for data scraping, analysis and visualization we used in building our EU Parliament activity research. We will go through the most interesting and challenging tasks we faced, as well as some of the mistakes we made during analysis and implementation, by displaying the code in a Jupyter Notebook environment. We will also refer to the projects and materials we used and conclude by inviting further discussion and collaboration on our publicly available project.

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Dario Radečić, Data Science, Algebra

WKS5 Real estate market price prediction tool

11:00 – 12:30 | Academy Room B
Fast recovery of real estate sector in Croatia in last months is powered by tourism and expected Croatian EU presidency. No matter of you are looking to buy or rent, to live in or to invest, real estate is one of the preferred investor strategies. With upcoming law related to property tax, our market can expect changes both in way how price will be calculated but also in way how different parts of Country will be further developed. With recent Airbnb ban from Paris/France aiming against real estate pricing trends, we can expect more and more policies to enter the market. If you wonder why data scientists are not covering this topic – wonder no more! As part of… (for more info press speaker photo)

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Vladimir Marković, IT Auditor, Banca Intesa Beograd, Serbia & Grozdana Marić, SAS

WKS3-2 How unsupervised machine learning help in fraud detection?

11:00 – 12:30 | Academy Room C
Steps in detecting collective anomalies using application logs in practice
o Data preparation
o Find behavioral patterns
o Make „fingerprint“ for each user
o Analyze the fingerprints and detect collective anomalies
Visualization of results
Some tips
Using results in SAS Fraud Solution


Coffee Break

12:30 – 13:00

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Badr Ouali, Data Scientist, Vertica

WKS6 Workshop on 3 use-cases showing the power of Vertica advanced analytics

13:00 – 14:30 | Academy Room A
• Introduction to Vertica-ML
• Geospatial + ML to predict golf players location and apply a marketing policy in their location (I explain what is possible with the geospatial library first and then I go to the use-case) – 30mns
• ML to catch fraudulent machines which are clicking a lot in a PPC system – 20mns
• Guess: Predicting clothes generation in order to segment customers – 20mns
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Arian Stipić & Tomislav Bronzin, CITUS

WKS7 I see you, I know who you are, what you want, and you cannot fool me!

13:00 – 14:30 | Academy Room B
There are many ideas about incorporating augmented reality in everyday applicative solutions, but very few practical examples currently exist. Most of them are primarily related to gaming industry and this workshop will show you how to implement real-life solutions based on this very advanced technology.
The solutions are built on Microsoft Kinect device support for stereoscopic real-time image recognition and analysis. These Kinect capabilities are then combined and integrated with other components in order to create lightning fast analysis and augmented reality experience for the end user.
Attendees will get the insight into the whole development process, see the practical demos and have the opportunity to discuss all aspects of presented solutions.