@misc{16744,
  author = {Cise Midoglu},
  title = {7 Things They Don{\textquoteright}t Tell You About Streaming Analytics},
  abstract = {The purpose of this talk is to debunk a number of streaming analytics myths, Ha-Joon Chang style.

We discuss 7 "thing"s which address common misconceptions ranging from marketing ploys (*ahem*), such as how we are all empowering our video analytics pipelines with AI, to legitimate confusions, such as what makes an appropriate QoE representation for a given stakeholder and/or use case.


	Thing 1: Streaming analytics is not only for debugging errors.
	Thing 2: The video community is not actually using AI for streaming analytics.
	Thing 3: What we talk about when we talk about QoE might be wildly different.
	Thing 4: We do not have enough standards for streaming analytics.
	Thing 5: Energy consumption should be a bigger concern for streaming analytics.
	Thing 6: Open source software and open datasets can also benefit commercial streaming analytics products.
	Thing 7: Streaming analytics is not ready for the metaverse.


We provide use cases, examples and lessons learned from both research and industry. Bite-sized takeaways guaranteed.},
  year = {2022},
  journal = {Demuxed {\textquoteright}22},
  url = {https://www.youtube.com/watch?v=0iWhuR9xDlw},
}