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
    big data and customer service outsourcing
    How Data Analytics Improves Customer Service Outsourcing
    18 Min Read
    How a Specialized Marketing VA Improves Campaign Analytics
    How a Specialized Marketing VA Improves Campaign Analytics
    11 Min Read
    New Data Analytics Breakthroughs Give eCommerce Startups a Fighting Chance
    New Data Analytics Breakthroughs Give eCommerce Startups a Fighting Chance
    6 Min Read
    How Data Analytics Is Reshaping Patient Financing Decisions
    How Data Analytics Is Reshaping Patient Financing Decisions
    13 Min Read
    business using business intelligence
    How to Use a Competitive Intelligence Dashboard to Turn Market Data Into Smarter Marketing Decisions 
    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

business intelligence
Business Intelligence: The Importance of Time to Value
Big Data and the SME: Prepare to Succeed
6 Ways Big Data Hadoop Is Helping America Become Energy Independent
Blog Maintenance
Government’s Big Data Affected by Shutdown

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

big data for non-QR lending in real estate
How Real Estate Investors Can Use Big Data for Non-QM Lending
Big Data Exclusive
ai video ad generation
How to Build High-Performing Ad Creatives with an AI Short Ad Video Maker?
Artificial Intelligence
big data and customer service outsourcing
How Data Analytics Improves Customer Service Outsourcing
Analytics Exclusive
The End of Unstructured Marketing: Forcing Generative AI into Strict HTML Schemas
The End of Unstructured Marketing: Forcing Generative AI into Strict HTML Schemas
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Image
AnalyticsBest PracticesCommentaryExclusiveKnowledge ManagementRisk ManagementSoftware

Technology Training Needs a Hands-On Approach

5 Min Read
Image
AnalyticsBig DataCommentaryExclusiveHardwareITLocationMobilitySecurity

Ramifications of IT Infrastructure Everywhere

6 Min Read
Image
AnalyticsCommentaryExclusiveHadoopITOpen SourceRisk ManagementUnstructured Data

Is Your IT Architecture Ready for Big Data?

5 Min Read
Image
CommentaryCulture/LeadershipExclusiveRisk ManagementStatistics

Problems with the Language of Probability

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.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
ai is improving the safety of cars
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?