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Big data is at least four different problems (2015) [video]

• klabb3 4y ago
  Paraphrased from description: - Large amounts of source data - Large amount of processing/analytics of data (ML and other models) - Large flow of data (data per time unit) - Diverse input sources (combining data from different sources and formats) Obviously these aren't mutually exclusive.
  • deleted 4y ago
    [deleted]
  • ypeterholmes 4y ago
    Thank you for parsing out this data
• jimcavel888 4y ago
• denimnerd42 4y ago
  Interesting he brings up zynga and their impressive petabytes worth of clicks. They weren't able to sustain a business off of that insight so was that a technology failure or a business model failure.
• dafelst 4y ago
  Can anyone recommend any articles/blogs/etc on big data success stories outside of ad tech and retail web tech? And I mean big, business defining successes. It's not to say they don't exist, obviously analytics is super important, but after being involved in it for 10+ years, it is rare that I have seen any game changing results come from big data analytics teams. Lots of small incremental improvements, sure, but I wonder about the ROI given the infra costs.
  • edmundsauto 4y ago
    Would you consider fintech or algorithmic trading a use case? Or analytics for sports? The sabermetric revolution uses big data for video analysis now - something like 6 TB per game. Flexport might be another example. Although I’m not privy exactly to how they use data.