VC view on IBM and Business Analytics

[Evangelos Simoudis is a former researcher in Data Mining/KDD, who founded a number of start ups, and is currently a Managing Director for Trident Capital focused on investments in Internet and software]

Last Tuesday I was invited to speak at an IBM event for technology bloggers. The event addressed two topics that represent key growth priorities for IBM: business analytics and smarter planet. ...

I was asked to talk about why VCs are interested today in business analytics. My presentation followed the talks of the three IBM executives who stated that:

1. Worldwide customer demand for business analytics services is so strong that IBM is now trying to hire an additional 3000 consultants...

2. IBM customers are starting to ask for Hadoop-based data warehousing and analytics solutions in order to determine if they can [use] them to a) manage and analyze large data sets more cost-effectively and b) to quickly perform exploratory data analyses on multi-dimensional data. However, the case studies provided by Rod Smith of IBM customers using Hadoop today were not dealing with big data (i.e., TB- or PB-scale data sets).

3. As part of its smarter planet initiative IBM continues to expand its collaboration with cities around the world where it applies business analytics and uses business processes from the corporate world in order to streamline and optimize the operations of cities.

4. Even after spending several billion on BI-related acquisitions, IBM intends to continue building out its business analytics technology stack through additional acquisitions and internal product development.

In my presentation I claimed that VCs are investing in business analytics for the following reasons:

1. The impact of cloud computing. Cloud computing is enabling the creation of new analytic applications, such as Infopia's ecommerce analytics application, ... where analytics are embedded in the application from the beginning rather than as an afterthought

2. The emergence of big data. Ever increasing volumes of structured and semi-structured data, including web data, such as that created by ad networks, and sensor data, such as that created by he Internet of Things, are starting to test the scalability of existing data warehousing solutions, make such solutions prohibitively expensive, and inhibit the timely creation of actionable analytics... I had written about the data volumes created by the web applications and how a new generation of analytic applications and data warehousing infrastructures need to be created in order to effectively deal with it here and here.

3. The need to analyze mobile and social data. The continuous growth of the mobile internet and commerce, as well as the accelerating growth of social internet and commerce create new sources of data and the need for new types of analytics.

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