Introduction to Data Streaming
In this talk, we'll define the context in which the old batch processing model was born, the reasons that are behind the new stream processing one, how they compare, discover pros and cons, and a list of existing technologies implementing the latter.
What you'll learn
While “software is eating the world,” those who are able to best manage the huge mass of data will emerge out on the top. The batch processing model has been faithfully serving us for decades. However, it might have reached the end of its usefulness for all but some very specific use-cases. As the pace of businesses increases, most of the time, decision makers prefer slightly wrong data sooner, than 100% accurate data later. Stream processing - or data streaming - exactly matches this usage: instead of managing the entire bulk of data, manage pieces of them as soon as they become available. In this talk, Nicolas Frankel will define the context in which the old batch processing model was born, the reasons that are behind the new stream processing one, how they compare, explore pros and cons, and outline existing technologies implementing the latter with their most prominent characteristics. Nicolas will conclude by describing one possible use-case of data streaming that is not possible with batches.
Table of contents
About the author
Big Data LDN (London) is a free to attend conference and exhibition, hosting leading data and analytics experts who are ready to equip you with the tools you need to deliver your most effective data-driven strategy. Discuss your business requirements with 130 leading technology vendors and consultants, hear from 150 expert speakers in 9 technical and business-led conference theaters, and network with thousands of fellow data experts.