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Dave Kellogg on Palantir

by alexandra on april 9th, 2010

I recently began reading the blog written by Dave Kellogg who is the CEO of Mark Logic, a company devoted to XML-based content management. I think I came to notice them when I discovered what cool technology EMC got when it bought X-hive which has now become Documentum xDb/XML Store. Mark Logic and X-hive was of course competitors in the XML Database market. In a recent blog post he reflects on the Palantir product after attending their Government Conference.

The main scope of his blog post is around different business models for a startup and that is not my expertise and I don’t have any particular opinion around that although I tend to agree and it was interesting to read his reflections of how other companies such as Oracle (yet another competitor to Mark Logic and xDb) have approached this.

Instead my thinking is based around his analysis of the product that Palantir offers and how that technology relates to other technology. I think most people (including Kellogg) mainly view Palantir as a visualisation tool because you see all these nice graphs, bars, timelines and maps displaying information. What they tend to forget is that there is huge difference between a tool that ONLY do visualisation and one that actually let you modify the data (actually modifying contextual data around them such as metadata and relations) within those perspectives. There are many different tools around Social Network Analysis for instance. However, many of them assumes that you already have databases full of data just waiting to be visualised and explored. Nothing new here. This is also what many people use Business Intelligence toolkits for. Accessing data in warehouses that is already their, although the effort of getting there from transactions oriented systems (like in retail) is not small in any way. However, the analyst using these visualisation-heavy toolkits access data read-only and only adds analysis of data already structured.

Here is why Palantir is different. It provides access to raw data such as police reports, military reports, open source data. Most of it in unstructured or semi-structured form. When it comes into the system it is not viewable in all these fancy visualisation windows Palantir has. Instead, the whole system rests on a collaborative process where people perform basic analysis which includes manual annotations of words in reports. This digital marker pen allows users to create database objects or connect to existing ones. Sure this is supported by automatic features such as entity extraction but if you care about data quality you do not dare to put them in automatic mode. After all this is done you can start exploring the annotated data and linkages between objects.

However, I do agree with Dave Kellogg that if people think BI is hard, this is harder. The main reason is that you have to have a method or process to do this kind of work. There are no free lunches – no point of dreaming about full automation here. And people need training and mindset to be able to work efficiently. Having played around with TIBCO Spotfire lately I feel that there is a choice between integrated solutions like Palantir which has features from many software areas (BI, GIS, ECM, Search etc) or using dedicated toolkits with your own integration. Powerful BI with data mining is best done in BI-systems whereas they probably never will provide the integration between features that vendors like Palantir offers. An open architecture based on SOA can probably make integration in many ways easier.


From → ECM, Technology

One Comment
  1. Thanks for discussing my post. I think you’ve made a good point that Palantir is a read/write system as opposed to a pure data visualization tool which can only visualize data coming from one of more databases.

    Having used the tool a bit, first person, at the event I clearly saw the read/write of the properties inspector (”browser”) and the graph (e.g., making links, etc.).

    It’s an important distinction. It doesn’t change my perception of them as a front-end tool primarily for graph-centered BI (i.e., relationship analysis), but I agree with the distinction.


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