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20.06. - Dienstag
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22.06.
Have you ever ordered a product on Amazon websites and, when the box arrived, wondered how you got it so fast, how much it would have cost Amazon, how much carbon it emitted and what kinds of systems & processes must be running behind the scenes to power the whole operation?
Let’s take a look behind the scenes and open the doors of Amazon Data and Analytics teams to explore how the combination of our people and our advanced algorithms are working together to deliver to our customers millions of…
What does it take to operationalize machine learning and AI in an enterprise setting? This seems easy but it is difficult. Vendors say that you only need smart people, some tools, and some data. The reality is that to go from the environment needed to build ML applications to a stable production environment in an enterprise is a long journey. This session describes the nature of ML and AI applications, explains important operations concepts, and offers advice for anyone trying to build and…
Missing data leadership, lack of vision, data-unliterate business units, data in silos, no data- and analytics-governance - The symptoms of a missing data strategy are unmistakable. Whilst organizations strive to exploit the benefits promised from data & analytics, corporate well thought data strategies are rather an exception than rule. We would like to exchange best practices and experiences for designing & implementing sustainable yet pragmatic data strategies for organizations.
Target…
Künstliche Intelligenz ist schon längst dem Pionierzeitalter entwachsen. Doch um mit dem Einsatz von KI einen echten Mehrwert für das Unternehmen zu schaffen, kommt es auf die qualitativ hochwertige Bereitstellung von Daten an. Hier kommt ML Engineering ins Spiel - ein Konzept zur Bewältigung der hohen Komplexität von Daten bei der Entwicklung von KI-Systemen. Im Vortrag wird eine ML Engineering Roadmap vorgestellt, mit der dieses häufig unterschätzte und doch so kritische Konzept erfolgreich…
As the data mesh paradigm takes the industry by storm, the conversation deep dives into the architecture, neglecting the socio-organizational element. Data driven organizations must invest not only in infrastructure but also data organization and culture.
Target Audience: Executive, senior business managers
Prerequisites: None
Level: Basic
The real magic of AI lays in well managed data to build and train the underlying models. Accordingly, streamlined data management process are essential for success in AI. In this session we are going to discuss data management for AI and ask questions like 'What is data management for AI?', 'Are there difference to well-known approaches from BI & Analytics' and 'Do we need special AI data engineers?'.
TDWI Community Talk is an open format to discuss current topics in the area of data analytics…
Machine learning and AI have changed the world of data processing and automation at a breathtaking pace, at the cost of turning algorithms into hard-to-control and monitor black boxes.
We present methods and concepts of explainable AI that aim to open the black box and tame these algorithms.
Target Audience: Decision-Makers/Stake Holders in AI & model development, Data Scientists
Prerequisites: general awareness of modeling pipeline and challenges, no coding/math skill required
Level: Basic
Natural Language Processing (NLP) allows us to deeply understand and derive insights from language, ultimately leading to more automated processes, lower costs, and data-driven business decisions.
Google is recognized as a market leader in AI and has built a range of solutions incorporating NLP to address a myriad of business challenges. This talk will introduce a few possible solutions, as well as some business use cases on how to incorporate them in a variety of industries.
Target Audience: M…
In order to succeed in creating a data driven enterprise it is clear that choosing the right data architecture is now critical. This session explores the evolution of data and analytics architecture and looks at what is needed to shorten time to value and create a data driven enterprise. It looks at the pros and cons of data lake, lakehouse and data mesh architectures and asks: Is there a best approach? Is a lot more than this needed to succeed?
Target Audience: Data architects, CDOs, CAOs,…
The data lakehouse is the new popular data architecture. In a nutshell, the data lakehouse is a combination of a data warehouse and a data lake. It makes a lot of sense to combine them, because they are sharing the same data and similar logic. This session discusses all aspects of data warehouses and data lakes, including data quality, data governance, auditability, performance, historic data, and data integration, to determine if the data lakehouse is a marketing hype or whether this is really…
Digital transformation is in a way a never-ending journey. Recent trends put high expectations on AI technologies for process automation, insight generation and decision support. In Hilti, we see information generated from our data as substantial contribution to the success of our business.
We will describe how we put the user and the usage of information in the center of our initiative of an information enabled company. Hilti’s journey towards process, data and system consolidation serves as…
At TDWI München Brian will hold a Workshop on "Designing Human-Centered Data Products". In this interview, he provides insights about what participants can expect in the workshop.
Henning Baars und Julian Ereht berichten über Ihr neues Seminar "Data Management 4 AI". Warum ist das Thema gerade jetzt so aktuell? Welche Inhalte behandeln die beiden in Ihrem Seminar? Und wie entsteht eigentlich ein TDWI-Seminar? Einblicke hinter die Kulissen der TDWI Seminare.
A popular new architecture for offering frictionless access to data is the data fabric. With a data fabric, existing transactional and data delivery systems are wrapped (encapsulated) to make all of them look like one integrated system. A data fabric enables all data consumers to access and manipulate data. Technically, data is accessed and used through services. But data fabrics cannot be bought, they need to be designed and developed. This session discusses key guidelines for designing data…
SWICA historically runs a data warehouse built by a centralized team and in parallel, multiple isolated solutions for domain specific analyses, which afford high maintenance and an extensive effort to stay compliant.
Modernizing our analytical environment, we are building a collaborative platform on MS Azure, utilizing the Data Mesh paradigms of data domain and data product.
We aim to deliver a managed data marketplace for all data domains to provide their data products on a modern platform with…
Petrol is Slovenian company that operates in 8 countries in SEE with 5BEUR annual revenue. As traditional publicly-owned company, Petrol has faced necessity for transformation to stay ahead in highly competitive market. Use of BIA was mainly reactive, but in recent years it has transformed into competitive advantage by using cloud technologies and industry specific analytical models and focusing on the content and creating business value. This value is now being leveraged as competitive…
Data Analysts and Data Scientists invest an immense amount of time into optimizing models and interpreting data, all in the quest to promote better business decision making and more efficient product development. We oftentimes however fail to take a step back and answer the overarching question: Why does the user show the observed behavior pattern? Why does a certain variable improve the accuracy of our prediction model? Despite all the advances we have made in analytics, even predictive…
For many years, technology gurus, transformation evangelists and many more have pictured a world that will dramatically change with incredible pace. Consequently, it was predicted that impacts on society, economy, environment, and political landscapes will leave no stone unturned. As a matter of fact, the current times feel as if these predictions have eventually become reality. The VUCA world is not only part of our daily life, but also even a nucleus in itself that demands resilience from…