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: Beware of Big Data Technology Zealotry
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Data Management > Best Practices > Beware of Big Data Technology Zealotry
AnalyticsBest PracticesBig DataCommentaryCulture/LeadershipData VisualizationData WarehousingExclusiveHadoopHardwareOpen SourcePredictive AnalyticsRisk Management

Beware of Big Data Technology Zealotry

paulbarsch
paulbarsch
5 Min Read
Beware of Big Data Technology Zealotry
Illustration generated with Qwen Image.
SHARE

Undoubtedly you’ve heard it all before: “Hadoop is the next big thing, why waste your time with a relational database?” or “Hadoop is really only good for the following things” or “Our NoSQL database scales, other solutions don’t.” Invariably, there are hundreds of additional arguments proffered by big data vendors and technology zealots inhabiting organizations just like yours. However, there are few crisp binary choices in technology decision making, especially in today’s heterogeneous big data environments.

Teradata CTO Stephen Brobst* has a great story regarding a Stanford technology conference he attended. Apparently in one session there were “shouting matches” between relational database and Hadoop fanatics as to which technology better served customers going forward. Mr. Brobst wasn’t amused, concluding; “As an engineer, my view is that when you see this kind of religious zealotry on either side, both sides are wrong. A good engineer is happy to use good ideas wherever they come from.”

Considering various technology choices for your particular organization is a multi-faceted decision making process. For example, suppose you are investigating a new application and/or database for a mission critical job. Let’s also suppose your existing solution is working “good enough”. However, the industry pundits, bloggers and analysts are hyping and luring you towards the next big thing in technology. At this point, alarm bells should be ringing. Let’s explore why.

First, for companies that are not start-ups, the idea of ripping and replacing an existing and working solution should give every CIO and CTO pause. The use cases enabled by this new technology must significantly stand out.

More Read

Mark Drapeau is the Epitome of Government 2.0
Mark Drapeau is the Epitome of Government 2.0
The Science of Crisis Communication
Examining Big Data’s Potential In Predictive Marketing
Data-Driven BPM: Making “Big Data” Actionable
Forecasting the Stock Market: Lessons Learned

Second, unless your existing solution is fully depreciated (for on-premises, hardware based solutions), you’re going to have a tough time getting past your CFO. Regardless of your situation, you’ll need compelling calculations for TCO, IRR and ROI.

Third, you will need to investigate whether your company has the skill sets to develop and operate this new environment, or whether they are readily available from outside vendors.

Fourth, consider your risk tolerance or appetite for failure—as in, if this new IT project fails—will it be considered a “drop in the bucket” or could it take down the entire company?

Finally, consider whether you’re succumbing to technology zealotry pitched by your favorite vendor or internal technologist. Oftentimes in technology decision making, the better choice is “and”, not “either”.  

For example, more companies are adopting a heterogeneous technology environment for unified information where multiple technologies and approaches work together in unison to meet various needs for reporting, dashboards, visualization, ad-hoc queries, operational applications, predictive analytics, and more. In essence, think more about synergies and inter-operability, not isolated technologies and processes.

In counterpoint, some will argue that technology capabilities increasingly overlap, and with a heterogeneous approach companies might be paying for some features twice. It is true that lines are blurring regarding technology capabilities as some of today’s relational databases can accept and process JSON (previously the purview of NoSQL databases), queries and BI reports can run on Hadoop, and “discovery work” can complete on multiple platforms. However, considering the maturity and design of various competing big data solutions, it does not appear—for the immediate future—that one size will fit all.

When it comes to selecting big data technologies, objectivity and flexibility are paramount. You’ll have to settle on technologies based on your unique business and use cases, risk tolerance, financial situation, analytic readiness and more.  

If your big data vendor or favorite company technologist is missing a toolbox or multi-faceted perspective and instead seems to employ a “to a hammer, everything looks like a nail” approach, you might want to look elsewhere for a competing point of view.

*Full disclosure: the author of this column is employed by Teradata Corporation.

TAGGED:risky business
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article explains that training robots for physical interaction requires three distinct data cate
Physical AI: What Data Do You Need to Train a Robot?
Artificial Intelligence Exclusive Robotics
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
Analytics Big Data Exclusive Software
Flat editorial illustration: The article examines AI agents that escalate from legitimate data retrieval to attempted intrusions
OpenAI’s Government Website Incidents Raise a Hard Question for AI Agents: When Should They Stop?
Artificial Intelligence News Security
Flat editorial illustration: The article's core relationship is the alignment between customer behavioral data (visit frequency,
Data-Driven Loyalty: How Restaurants Use Behavioral Analytics to Optimize Revenue
Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Is Your IT Architecture Ready for Big Data?
AnalyticsCommentaryExclusiveHadoopITOpen SourceRisk ManagementUnstructured Data

Is Your IT Architecture Ready for Big Data?

5 Min Read
Hygienic Hadoop Data Lakes Not Just Happenstance
CommentaryData ManagementExclusiveHadoopOpen SourcePolicy and Governance

Hygienic Hadoop Data Lakes Not Just Happenstance

4 Min Read
Is the Purpose of Analytics Just to Turn a Buck?
AnalyticsBest PracticesBig DataCollaborative DataCulture/LeadershipExclusiveMobilityModelingPredictive AnalyticsSocial Data

Is the Purpose of Analytics Just to Turn a Buck?

4 Min Read
When is CAPEX Coming Back?
Cloud ComputingCommentaryExclusiveHardwareIT

When is CAPEX Coming Back?

4 Min Read

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

How To Get An Award Winning Giveaway Bot
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

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?