The Hidden Costs of Cloud Data Lakes

This blog series from Cazena's engineering team investigates the hidden costs of cloud data lakes. Learn the top three hidden costs of cloud data lakes!

Read the Blog Series

a16z Interview – Big Data in the Cloud

Last week, Michael Copeland of Andreessen Horowitz interviewed me and Peter Levine, General Partner at  Andreessen Horowitz, on the topic of big data moving from on-prem infrastructure to the cloud.

It was a fun chat after we literally took over Peter’s office while he was attending a board meeting! In the interview, Peter, Michael and I discuss how:

  1. Big Data 1.0 evolves to Big Data 2.0 when you have rapid and frictionless access to data. Cloud enables this. We call it Big Data on Demand. 
  2. The Big Data stack is complicated because it has a diverse set of technologies that are being driven by a thriving open-source community. Enterprises should not look for one silver bullet for all workloads. Each technology has a sweet spot in terms of price-performance. 
  3. The move to the cloud requires two big issues to be overcome, friction (see #1 above) and complexity (see #2). Big Data as a Service is the new way to do so. 
  4. For the cloud to be the next platform for analytical data processing, data must “land” on the cloud and process multiple workloads. Moving back and forth is painful. Avoid this. 
  5. Big Data 2.0 helps pool data and spread it around faster. It will amplify the signal from the noise. For organizations large and small, it will create a data-driven culture. 
  6. Peter has an interesting vision of application-aware Big Data 3.0 that ultimately derives from Big Data 2.0. 

See the full interview below, read the full transcript, or download the podcast.


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