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Data… Network… Action!

Cisco’s acquisition of Composite Software begins to bear fruit.

FogSanFranLast Friday, the Cisco / Composite crowd turned up at the #BBBT. And I do mean crowd; seven participants from Cisco were present, including four speakers. Even a full year after its acquisition by Cisco, the Composite name still lingers for me at least, even though the Cisco branding and technical emphasis were on full view.

A major portion of this year’s session focused on Cisco’s vision of an architectural framework to enable the Internet of Things (IoT) or, in Cisco’s own words, the Internet of Everything. This fascinating presentation by Jim Green, former Composite CEO and now CTO of the Data and Analytics Business Group at Cisco, provoked extensive discussion among the members. Unfortunately for readers of this post, the details are under NDA, but I look forward to writing about them in the future. However, as a teaser, I will say this. Given the enormous growth predicted in the number of sensor-enabled devices—some 50 billion by 2020—our current data warehouse and big data architectures, which focus on centralized storage and manipulation of data, will need to be significantly augmented with real-time, streaming processing distributed throughout the network to simply cope with the volumes of data being generated. I even learned a new marketing buzzword—fog computing… to bring the cloud down to earth!

For BBBT old-timers, like me, our primary interest remains data virtualization, particularly as it relates to BI, and how the acquisition helped or hindered the development of that core function. One fear I had is that this small element of a bigger picture could get lost in the big corporation messaging of Cisco. That fear remains. For example, it took me quite some time to find the “Composite portion” of the Cisco website… it’s here, if you want to bookmark it. This is an aspect of the merged positioning that needs more attention.
But what about data virtualization? Virtualization function is a mandatory component of any modern approach to business intelligence and decision making support. It is a key component (under the name reification) of the process space of my Business unIntelligence REAL architecture. BI folks always focus on the data, of course. But, there’s much more to it.

Here’s what I wrote last year soon after the acquisition and last BBBT Cisco / Composite appearance: “One of the biggest challenges for virtualization is to understand and optimize the interaction between databases and the underlying network. When data from two or more distributed databases must be joined in a real-time query, the query optimizer needs to know, among other things, where the data resides, the volumes in each location, the available processing power of each database, and the network considerations for moving the data between locations. Data virtualization tools typically focus on the first three database concerns, probably as a result of their histories. However, the last concern, the network, increasingly holds the key to excellent optimization… And who better to know about the network and even tweak its performance profile to favor a large virtualization transfer than a big networking vendor like Cisco? The fit seems just right.” (See the full blog here.)

Clearly, this work is progressing with combined hardware/software offerings based on the Cisco (was Composite) Information Server and Cisco’s server and router offerings, although little was provided by way of technical detail or performance claims. Within the data virtualization space itself, the emphasis is on two key aspects: (1) to simplify the use and adoption of data virtualization and (2) to expand data virtualization sources particularly for big data and the Internet of Things. While these two aspects can be taken separately, I believe that it is in their combination that most benefit can be found. It has long been clear to me that big data and IoT data do not belong in the traditional data warehouse. Nor does it make sense to move business transaction data from well-managed relational environments to Hadoop—the Data Lake approach. (In my view, copying legally binding transaction and contractual data into a loosely defined and poorly controlled Data Lake risks corrupting and losing control over vital business assets.)

Virtualization across these two environments, and others, is the most sensible—and perhaps only possible—way to enable business users to combine such very different types of data. Furthermore, providing users with the ability to understand and use such combined data through abstraction and directory services is vital. So, the direction articulated by the Cisco Data and Analytics Business Group brings together two of the vital components to address the growing need for business users to understand, find and combine information from traditional and (so-called) big data sources. A grand challenge, indeed…

I look forward to Cisco’s Data Virtualization Day in New York on 1 October, from where I expect to report further developments on this interesting roadmap.

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