The data & analytics market has changed over the last years. In between, probably also driven by the pandemic, we can observe a strong development. In their keynote presentation at the DATA festival event in May 2022 live in Munich, Data Festival founders Dr. Carsten Bange and Alexander Thamm – both experienced experts and thought leaders in the industry – gave an exciting overview of the developments of recent years and actual trends.
“During the last 2-3 years we saw some paradigm shifts and that the industry of AI, Machine Learning, Business Intelligence, Data and Analytics is converging.”, Alex introduced the presentation.
Watch their keynote here:
From Prototypes to Data & MLOps: Getting the Machine Learning running and creating value from it is hard work. Nevertheless, many companies presented their experiences on this topic at the DATA festival. This is consistent with the observations that this hot topic didn’t slow down but accelerated during the pandemic.
From Data Warehouse to Data Fabric: Behind this is a change in paradigm and the way of thinking about how we physically store data. Data Warehouse is not going away, although not the data lakes or the data lakehouses – do we need to bring all data to one location? No. Because it’s too much data. So the data fabric has also become an important topic that defines a more adaptable, flexible and safe data architecture.
From Black Box to Explainable AI: We need to create explainable models to create a trust to have the people use the model. Because a running system is important but a running system that nobody uses doesn’t even create value.
From Data Kingdoms to Data Democracy: One thing in a company’s data strategy is still often missing: the data culture. How to bring “data to live”, how to reach employees to engage with data and make data an everyday concern. So we need to make data more accessible and democratize it.
From Unicorns to Teamwork: In the past, there were the unicorns – the data scientists. Today we have teams with very different types of roles working in the fields of data and AI because this is not any more only a topic for IT but also for others like e.g. business analysts, business enablers, data strategists, industry experts, and so on to leverage the ideas and to drive data strategy and AI in the company.
From Data Lab to Data Mesh: Data Mesh is an organizational concept that is about bringing data-knowhow into the business departments, building the data products there and finding the right balance between what to centralize and what to decentralize.
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