Distributed Systems

•August 28, 2014 • Leave a Comment

Few interesting articles recently on distributed systems:

  • The Space Between Theory and Practice in Distributed Systems
  • Distributed systems theory for the distributed systems engineer

Of particular interesting:

How you decide whether an event happened before another event in the absence of any shared clock. This means Lamport clocks and their generalisation to Vector clocks, but also see the Dynamo paper.

And then there is the coolness of state machines:

Distributed state machine replication (Wikipedia is ok, Lampson’s paper is canonical but dry).

 

Legacy Data

•August 27, 2014 • Leave a Comment

Dave McCrory has an interesting presentation on InfoQ which discusses enterprise platform as a service.  Slide 23 onwards discusses legacy data, and the issues associated with data consumption.  Master Data Management is also discussed in the deck.  Which leads to a New York Times article, “For Big-Data Scientists, ‘Janitor Work’ Is Key Hurdle to Insights”.

Data scientists, according to interviews and expert estimates, spend from 50 percent to 80 percent of their time mired in this more mundane labor of collecting and preparing unruly digital data, before it can be explored for useful nuggets.

 

 

Capital Market Big Data Use Cases

•August 27, 2014 • Leave a Comment

Couple of interesting use cases in this InfoQ video:

  • Broker-Dealer transaction history
  • Client Review
  • Customer Relations and Prospecting
  • Enterprise Credit Risk
  • Cluster Pricing

Clearly the presentation didn’t have time to get into Lambda architectures, Spark and more

Open Bank Project

•August 26, 2014 • Leave a Comment

Interesting video on InfoQ on Open Bank Project – retail banking.  In many ways its similar to Bloomberg’s App Portal initiative.

Python and Big Data

•August 19, 2014 • Leave a Comment

Coupled of interesting video’s from EuroPython:

  • Python’s Role in Big Data Analytics: Past, Present, and…
  • Big Data Analytics with Python using Stratosphere
  • Scalable Realtime Architectures in Python

 

Dynamic Time Warp

•August 15, 2014 • 1 Comment

Interesting read over on Systematic Investor, “Time Series Matching with Dynamic Time Warping”.  Would be interesting to apply DTW against trading recommendations.   Another paper on DTW also looking interesting: Trading Strategies based on Pattern Recognition in Stock Futures Market using Dynamic Time Warping Algorithm.  Likewise: Patterns In Financial Markets:dynamic Time Warping

Price Margining using Logistic Regression and Spark

•August 11, 2014 • Leave a Comment

Insight offered an interesting read on logistic regression and spark.  Which lead to the thought if one could track binary classification and predict a spread at which a client might hit a quote via an RFQ, RFS or ESP.   Interesting

 
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