We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Big Analytics Rather Than Big Data
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Big Analytics Rather Than Big Data
Uncategorized

Big Analytics Rather Than Big Data

Barry Devlin
Barry Devlin
4 Min Read
Big Analytics Rather Than Big Data
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

The past year has been dominated by Big Data.  What it might mean and the way you might look at it. The stories have often revolved around Hadoop and his herd of chums.

The past year has been dominated by Big Data.  What it might mean and the way you might look at it. The stories have often revolved around Hadoop and his herd of chums. Vendors and analysts alike have run away and joined this ever-growing and rapidly moving circus. And yet, as we saw in our own EMA and 9sight Big Data Survey, businesses are on a somewhat different tour. Of course, they are walking with the elephants, but many so-called Big Data projects have more to do with more traditional data types, i.e. relationally structured, but bigger or requiring faster access. And in these instances, the need is for Big Analytics, rather than Big Data. The value comes from what you do with it, not how big it happens to be.

Which brings us to Big Blue.  I’ve been reading IBM’s PureSystems announcement today.  The press release headline trumpets Big Data (as well as Cloud), but the focus from a data aspect is on the deep analysis of highly structured, relational information with a substantial upgrade of the PureData for Analytics System, based on Netezza technology, first announced less than four months ago.  The emphasis on analytics, relational data and the evolving technology is worth exploring.

Back in September 2010, when IBM announced the acquisition of Netezza, there was much speculation about how the Netezza products would be positioned within IBM’s data management and data warehousing portfolios that included DB2 (in a number of varieties), TM1 and Informix. Would the Netezza technology be merged into DB2?  Would it continue as an independent product?  Would it, perhaps, die? I opined that Netezza, with its hardware-based acceleration, was a good match for IBM who understood the benefits of microcode and dedicated hardware components for specific tasks, such as the field programmable gate array (FPGA), used to minimize the bottleneck between disk and memory. It seems I was right in that; not only has Netezza survived as an independent platform, as the basis for the PureData System for Analytics, but also being integrated behind DB2 for z/OS in the IBM DB2 Analytics Accelerator.

More Read

Information Optimization Is a Key Benefit of Big Data Investments
Information Optimization Is a Key Benefit of Big Data Investments
Is Predictive Analytics Setting The Stage For An Ethereum Price Increase?
Using Data to Plan Safer, More Efficient Public Playgrounds
Why are Personal and Organizational Changes Still Failing?
Big Data

Today’s announcement of the PureData System for Analytics N2001 is, at heart, a performance and efficiency upgrade to the original N1001 product, offering a 3x performance improvement and 50% greater capacity for the same power consumption. The improvements come from a move to smaller, higher capacity and faster disk drives and faster FPGAs. With a fully loaded system capable of handling a petabyte or more of user data (depending on compression ratio achieved), we are clearly talking big data. The technology is purely relational. And a customer example from the State University of New York, Buffalo quotes a reduction in run time for complex analytics on medical records from 27 hours to 12 minutes (the prior platform is not named). So, this system, like competing Analytic Appliances from other vendors, is fast.  Perhaps we should be using images of cheetahs?

[The photo is from my visit to Addo Game Reserve in South Africa last week.  For concerned animal lovers, she did eventually manage to climb out…]

TAGGED:analyticsbig analyticsbig datacloudhadoopibmnetezzaPureData System for Analytics
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article connects fragmented social-service records through shared pathways and selective informa
Turning Disconnected Information Data Into Better Social Service Outcomes
Big Data
Flat editorial illustration: The article explains how one KYC upload becomes separate records held by a verification vendor and a
What Happens to My KYC Data Behind the Approval Screen?
Big Data Exclusive
Flat editorial illustration: The article connects AI-generated avatar variants with disciplined, measurable video experiments. A
How to Use an AI Avatar Generator to Run Measurable Video Experiments
Artificial Intelligence Exclusive
Flat editorial illustration: The article’s core relationship is between growing compute density and adaptable rack hardware that
6 Details That Make a Data Centre’s Server Room Easier to Scale
Best Practices Data Management Exclusive IT

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

big data and vpn
Big DataPrivacy

5 Incredible Ways Big Data Has Made VPNs Powerful Privacy Tools

8 Min Read
Text Analytics Pros Daily
Business Intelligence

Text Analytics Pros Daily

2 Min Read
big data and client communication
Big DataExclusive

4 Ways Big Data And Client Communication Technology Help Companies

6 Min Read
Defending Your Analytics: Handling Hecklers
Business IntelligenceCRMData MiningExclusiveInside CompaniesMarketingPredictive Analytics

Defending Your Analytics: Handling Hecklers

9 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
How To Get An Award Winning Giveaway Bot
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?