Program

Data monetization: Data as a raw material for data products

Ondřej Tomas, CEO & Co-Founder, CleverMaps

Like most ingredients, also the data needs to be adjusted before final consumption. Business consumers don't like raw data and don't see its true value. To better monetize data and use it in business situations, it must turn into a product with a clear purpose, features, price and presentation. This is associated with a number of questions: How to understand the flood of data offered? How to verify the security and quality of data? We will show a comparison of raw data and final data products, including their use for creating data stories.

Payment data - from its cleaning to use

Ivan Dovica, Co-Founder, Dateio

When we founded Dateio years ago, we realized that banks dispose of a large amount of data, but often it is not even clear where the client has paid. This is really not how we imagined the "data age. Without high-quality input data, it is impossible to make quality decisions and build algorithms. That is why we have gradually built a service that provides detailed information about payments and is used by banks around the world. We will also document how the enrichment of data has fundamentally changed its value and potential for use.

Data Geoanalytics

Petr Paščenko, Head of Data Science, Profinit

In the open data domain, there are a number of interesting data sources focused on geographic data. The combination of these data creates a plastic image of the Czech Republic and its inhabitants. Using analytical methods of machine learning, it is possible to obtain a number of non-trivial insights and valuable data for strategic decisions in the public and commercial spheres.

Optimization of warehouse processes based on data

Martin Kavřík, Head of Data Office, Notino

Warehouse processes have a great influence on the success of any e-commerce project, because they affect both a significant part of the costs and the customer experience through the speed of delivery. If you want to learn how to use data to streamline warehouse processes, increase the availability of goods and speed up their delivery, come and see our lecture.

Data and business procrastination

Martin Hošek, Sales Manager, Imper

Data is the spell of the times. Their inexhaustible number and often unorganized need for endless analyses leads to the loss of their primary benefit – efficiency. The decisive factor is not the amount of information, but its relevance, time and context. How to tame the wild waters of "smart data" by using modern tools and procedures for their use and integration?

Google Looker from the perspective of Tableau analyst

Michal Charvát, Data Practice Lead, KINDRED

Let's face it – Google doesn't pay us for this presentation :). For the first time, we had the opportunity to participate in the implementation of Looker as a tool for a complete solution of corporate reporting and self-service BI. Since we mostly work with Tableau or PowerBI, we noticed some interesting differences in the approach of these tools to working with data and visualizing it. And it's not just about the existence of LookML. We will show what an organization that would consider switching to Looker must count on and how its approach to Business Intelligence can change.

From cash register to Internet, or analysis of (not only) e-shop data

Kryštof Kadlec, Consultant, Sophia Solutions

One of the areas that has grown significantly in recent years is the area of e-shops. Their number, size, and thus the volume of data they possess and which deserves analysis has increased. The right decisions need to be backed up by data, appropriate views of them and their skilful interpretation. How Sophia Solutions can help with it will be shown on simple examples.

Experience with searching for anomalies in the big data of an industrial enterprise

Jiří Gregor, Board Member, Plastika

Tomáš Fürst, Data Science teacher and scientist, Přírodovědecká fakulta UPOL

We will describe the experience with searching for anomalies in process data. The general goal of anomaly search is to understand when something undesirable is happening in the process. You can either detect anomalies retrospectively to teach the algorithm to "understand" the structure of process data, understand the context, or uncover the causes, or we can detect anomalies in real time to prevent their unfortunate consequences. During our cooperation, we gained interesting experience in an interdisciplinary team consisting of technologists and other specialists of the manufacturer of complex parts for automotive, university experts in the field of statistics, AI and top developers.

IoT harvester from DEL – collection and processing of information in difficult terrain

Jan Haken, Business Development Manager for Global Compute, Dell Technologies

How to reliably collect and evaluate information in harsh conditions? In industry, in vehicles, in ore mines or on oil platforms? In these places, you can await many pitfalls, which will test the quality of your designs and, most importantly, the durability of the armament. Are you ready?

Data as a tool to accelerate the transition to sustainable agriculture

Vojtěch Malina, CEO, CleverFarm

The constant waste of water, fertilizers or chemical sprays with a negative impact on the soil, the environment or people motivates us at CleverFarm to work on a platform that teaches farmers to make decisions based on data, and not only on the basis of previous experience. We will show concrete examples of how we are able to reduce agricultural inputs and at the same time increase yields.

Data and its integration into everyday life has resulted in the necessity of digital transformation of companies and institutions. If an enterprise wants to prosper in the future and make the work of its employees easier, it is an imperative to maximize the use of data and their hidden information in company processes. They must not only harvest the data, but also sort it correctly, and most importantly "produce" strategic information for informed decisions. A discussion panel composed of a varied structure of experts will give us a chance to compare the efficiency of work with data in different sectors.

Participants:
Pavel Bulowski, Co-Founder and Chief Product Officer, Meiro
Radek Hájek, BI Manager, Kofola
Radovan Jirka, Data Detective, BizzTreat
Karel Macek, Senior AI/ML Architect, Generali Česká pojišťovna
Radovan Parrák, Head of Data, Alza