Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 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
Image
SHARE

Image

Image

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.”

More Read

Data warehouse architecture that’s too narrowly focused
Log Analytics Practices That DevOps Experts Must Embrace In 2019
Prinicpal Components for Modeling
Naming and Classifying: Text Analysis Vs. Text Analytics
Winners of Mozilla Open Data Competition announced

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.

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

macro intelligence and ai
How Permutable AI is Advancing Macro Intelligence for Complex Global Markets
Artificial Intelligence Exclusive
warehouse accidents
Data Analytics and the Future of Warehouse Safety
Analytics Commentary Exclusive
stock investing and data analytics
How Data Analytics Supports Smarter Stock Trading Strategies
Analytics Exclusive
qr codes for data-driven marketing
Role of QR Codes in Data-Driven Marketing
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Image
AnalyticsCommentaryExclusiveITPredictive Analytics

IT Doesn’t Matter… Until It Does

5 Min Read
Image
AnalyticsCommentaryExclusiveModelingPredictive AnalyticsWorkforce AnalyticsWorkforce Data

The Math Says Yes, But Human Behavior Says No

6 Min Read
Image
AnalyticsCloud ComputingCommentaryCulture/LeadershipData MiningExclusiveIT

The Dirty (Not so Secret) Secret of IT Budgets

4 Min Read
Image
CommentaryExclusive

Wasted Breath: Data Alone Won’t Convince

5 Min Read

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

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?