« #DMSLondon - What Will Drive Data Management? | Main | #DMSLondon - The Chief Data Officer Challenge »

07 October 2013

#DMSLondon - Big Data, Cloud, In-Memory

Andrew Delaney introduced the second panel of the day, with the long title of "The Industry Response: High Performance Technologies for Data Management - Big Data, Cloud, In-Memory, Meta Data & Big Meta Data". The panel included Rupert Brown of UBS, John Glendenning of Datastax, Stuart Grant of SAP and Pavlo Paska of Falconsoft. Andrew started the panel by asking what technology challenges the industry faced:

  • Stuart said that risk data on-demand was a key challenge, that there was the related need to collapse the legacy silos of data.
  • Pavlo backed up Stuart by suggesting that accuracy and consistency were needed for all live data.
  • Rupert suggested that there has been a big focus on low latency and fast data, but raised a smile from the audience when he said that he was a bit frustrated by the "format fetishes" in the industry. He then brought the conversation back to some fundamentals from his viewpoint, talking about wholeness of data and namespaces/data dictionaries - Rupert said that naming data had been too stuck in the functional area and not considered more in isolation from the technology.
  • John said that he thought there were too many technologies around at the moment, particularly in the area of Not Only SQL (NoSQL) databases. John seemed keen to push NoSQL, and in particular Apache Cassandra, as post relational databases. He put forward that these technologies, developed originally by the likes of Google and Yahoo, were the way forward and that in-memory databases from traditional database vendors were "papering over the cracks" of relational database weaknesses.
  • Stuart countered John by saying that properly designed in-memory databases had their place but that some in-memory databases had indeed been designed to paper over the cracks and this was the wrong approach, exascerbating the problem sometimes.
  • Responding to Andrew's questions around whether cloud usage was more accepted by the industry than it had been, Rupert said he thought it was although concerns remain over privacy and regulatory blockers to cloud usage, plus there was a real need for effective cloud data management. Rupert also asked the audience if we knew of any good release management tools for databases (controlling/managing schema versioning etc) because he and his group were yet to find one. 
  • Rupert expressed that Hadoop 2 was of more interest to him at UBS that Hadoop, and as a side note mentioned that map reduce was becoming more prevalent across NoSQL not just within the Hadoop domain. Maybe controversially, he said that UBS was using less data than it used to and as such it was not the "big data" organisation people might think it to be. 
  • As one example of the difficulties of dealing with silos, Stuart said that at one client it required the integration of data from 18 different system to a get an overall view of the risk exposure to one counterparty. Stuart advocated bring the analytics closer to the data, enabling more than one job to be done on one system.
  • Rupert thought that Goldman Sachs and Morgan Stanley seem to do what is the right thing for their firm, laying out a long-term vision for data management. He said that a rethink was needed at many organisations since fundamentally a bank is a data flow.
  • Stuart picked up on this and said that there will be those organisations that view data as an asset and those that view data as an annoyance.
  • Rupert mentioned that in his view accountants and lawyers are getting in the way of better data usage in the industry.
  • Rupert added that data in Excel needed to passed by reference and not passed by value. This "copy confluence" was wasting disk space and a source of operational problems for many organisations (a few past posts here and here on this topic).
  • Moving on to describe some of the benefits of semantic data and triple stores, Rupert proposed that the statistical world needed to be added to the semantic world to produce "Analytical Semantics" (see past post relating to the idea of "analytics management").

Great panel, lots of great insight with particularly good contributions from Rupert Brown.

TrackBack

TrackBack URL for this entry:
http://www.typepad.com/services/trackback/6a00e550575fab8833019affcf7708970b

Listed below are links to weblogs that reference #DMSLondon - Big Data, Cloud, In-Memory:

Comments

The comments to this entry are closed.

Xenomorph: analytics and data management

About Xenomorph

Xenomorph is the leading provider of analytics and data management solutions to the financial markets. Risk, trading, quant research and IT staff use Xenomorph’s TimeScape analytics and data management solution at investment banks, hedge funds and asset management institutions across the world’s main financial centres.

@XenomorphNews



Blog powered by TypePad
Member since 02/2008