TechnoPolitics Podcast: Big Data Is Value At Extreme Scale

Big Data is about handling extremes, cost effectively. But, what it means to be "big" is an upwardly moving target. In this episode of TechnoPolitics, Mike Gualtieri speaks with Forrester Principal Analyst Brian Hopkins about big data. Brian covers emerging technology and its impact on business and IT. 

Podcast Listening Options

Click here to download entire Forrester TechnoPolitics MP3 file

Next Episode - Windows 8: Bold Move Or Catch-Up?

Be sure to catch the next episode of TechnoPolitics to hear Forrester Vice President Frank Gillett's analysis of what Windows 8 means to Microsoft, consumers, and businesses. Frank's analysis of Microsoft Windows 8 will blow your mind. Microsoft is faced with its biggest challenge ever. Is Windows 8 the answer, a first step on the path, or will it fall flat?

About Forrester TechnoPolitics

Make the tough calls. That is what independent insight and analysis is all about. Hosted by Mike Gualtieri, Forrester TechnoPolitics features independent analysis and commentary from Forrester analysts about hot technology and what it means to you and the world. Scripted? Absolutely not. Passionate? We live it every day. Courage to make the tough calls? You be the judge.

Producers: Rachel Brown, Rowan Curran, and Nick Welles


Great Intro to Big data


I think this is a great into to Big data, especially the 2*2 matrix you had mentioned kind of nails the soft boundaries that differentiate the various technologies into specific use cases.

I have heard people mentioning Big data Technologies fitting 3 major themes, New capabilities, Cost reduction , Performance improvements. Is that how you would see as well in terms of organizations with existing DW/BI platforms adopting Big data ?.


Big Data storage, processing, and access

Hi Rajeev,

Thanks for listening to the podcast. I think the three themes you mentioned: new capabilities, cost reduction, and performance improvement are all important for organizations with existing DW/BI platforms. I'll give an example for each.

1. For new capabilities, we see organizations wanting to do more sophisticated text mining of unstructured data. For example, I spoke with a health care provider that wants to find patterns in medical records to improve care and reduce cost.

2. For cost reduction, Hadoop and other distributed storage technology on commodity hardware is a real game changer since it mostly cost less. However, this does not mean that organizations should go exclusively to Hadoop. Enterprise data warehouses are great for blazing fast queries - especially those that involve aggregates such as needed for visualizing data in real-time and fast data mining.

3. Performance is always in the race when it comes to Big Data. NOSQL databases like MongoDB are fast and flexible for data that has changing schema, but would be slower for arbritrary queries.

The data landscape is getting more complicated, but necessarily so. For firms to store, process, and access Big Data they need myriad technologies.

Here are two Big Data posts I did earlier that you may find interesting:

What Is Your Big Data Score
Let Big Data Predictive Analytics Rock Your World


Great Info...

Well dude, Big Data Is Extreme Data. TechnoPolitics interview with Forrester Principal Analyst Brian Hopkins @ Thanks for sharing.

Patricia Hall -