Everything You Need to Know About Big Data: From Architectural Principles to Best Practices
Ғылым және технология
In this session, we discuss architectural principles that help simplify big data analytics. We'll apply principles to various stages of big data processing: collect, store, process, analyze, and visualize. We'll discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
Пікірлер: 13
I'm only nine minutes in and this is clearly an excellent presentation. Clear, concise, and sufficiently broad for those coming fresh to the topic. Well done! Just finished. If you want to know about AWS and Big Data. This is the most worthwhile 45-minute presentation you will watch!
That was so good, at the end I clapped from my desk at home :)
Extremely Helpful, a succinct overview of AWS offerings...Thanks for this piece.
Well, I am a bigdata architect and recently joined a fintech- this video help me understand aws services and how to use it for my project.
I'm completely absorbed in this. I had the privilege of reading something similar, and I was completely absorbed. "Mastering AWS: A Software Engineers Guide" by Nathan Vale
succinct presentation on Big Data services in AWS
Fantastic presentation.
Can you share the slides
As far as I know and aws documentation mention, Kinesis data Stream and Firehose are not storage services . They used for data ingestion for streaming data . Those data then either pulled or pushed to storage services such as S3 or redshift or others . Seems this video has messed concept altogether and confusing .
@tom_see
2 жыл бұрын
kinesis streams can store the streaming data for as long as we need, of course 99% of use-cases would like to read this data in from the stream ASAP, but it's still technically storing the data: an example of this is how we can reprocess the same kinesis stream of data over and over if we choose, from the very beginning (as long as the data is still stored, based on the data lifetime setting)
The title is very misleading... This video is basically a sales presentation of all the Amazon Services. If you are new to Big Data this video will not really help you.
@awssupport
7 ай бұрын
Sorry to hear about this friction. Our teams care about opportunities you spot for improvement, which is why I've reached out internally to have your feedback reviewed and considered further. If you're interested, check out this Big Data info: go.aws/47E9x6H. For more tutorials and training on the topic, please explore the options here: go.aws/3GuQuQ2. ^JM
@et4493
3 ай бұрын
Yup