Kategorie: Data Products
My top takeaways from the Berlin AI Summit: Understand the problem and don’t neglect operations.
The major challenges to AI implementation are often mind-set based rather than technical. Problems in production and implementation of AI often stem from organizations‘ and practitioners‘ lack of ability and/or desire to thoroughly scope out and define the problem they are trying to solve. Consequently, they often don’t select the right tools, capabilities and processes to implement successfully. Organizations can also negelct operations (such as MLOps), which are important for work efficacy and scale.
Data Festival 2022: Democracy, Mesh, Fabric
The industry seems to be disillusioned by centralized data assets, data warehouse and data lake alike and looking for the next big thing.
Take aways from Big Data World, May 2022
The right mix of governance and freedom in architecture is still up for debate, end-to-end solutions are often-heard recommendations, low and no-code is expanding access to data and the customer journey could be seen as a source of revenue are some insights I gleaned from this spring’s Big Data World.
Julian and the robot- Next-gen user experience (UX) gets social
What can we learn about robotics, artificial intelligence and how UX will evolve into the architecture of social-emotional experiences?
Data-as-a-Service lessons from the company that was right about Trump
One South African company correctly predicted both the outcome of the Brexit vote and Trump’s victory. BrandsEye delivered a Data-as-a-Service (DaaS) product, amalgamating social media analysis, geolocation data and other inputs to create impactful insight that most pollsters missed.
What is Data-as-a-Service?
Data-as-a-Service (DaaS) can be described as productized data-driven insight on demand. DaaS allows business users to access the data and insights they need at the timing they desire. The data and insights can be consumed by multiple individuals simultaneously, location-independent of where the data has been sourced and managed.
Turning Big Data Disillusionment into Opportunity with Data-as-a-Service Products
Big Data’s descent from the peak of inflated expectations into the trough of disillusionment made a splash when Gartner came out with its 2016 Hype Cycle for Business Intelligence and Analytics. This stage is decisive: Big Data either delivers, and so rises a bit further up the slope of enlightenment