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 analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: OLAP is Dead (Long Live Analytics)
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Predictive Analytics > OLAP is Dead (Long Live Analytics)
Business IntelligencePredictive Analytics

OLAP is Dead (Long Live Analytics)

Timo Elliott
Timo Elliott
5 Min Read
SHARE

olap_is_dead_banner

The term OLAP or Online Analytic Processing was coined in 1993 by relational database technology pioneer Ted Codd (my claim to fame: we went to the same high school, Poole Grammar).

The term was chosen to contrast with OLTP or online transaction processing, and was prompted by some clever marketing folks at Essbase, who wanted to promote their multidimensional database product. Codd was famous for his twelve rules defining the relational model and duly came up with twelve rules for analytic systems.

The term was quickly taken up by the rest of the industry, and spawned new definitions (Nigel Pendse’s FASMI test) and multiple variations (MOLAP, HOLAP, ROLAP, Huey, Dewie and Louie, etc.) … 

More Read

Singapore
Keeping Singapore Green with Data and Design
Match Mitigation: When Algorithms Aren’t Enough
Approaches to Big Data Visualization
Enterprise Portfolio Management – back to basics
Harnessing the Power of Big Data, Machine Learning, & Predictive Analytics



olap_is_dead_banner

The term OLAP or Online Analytic Processing was coined in 1993 by relational database technology pioneer Ted Codd (my claim to fame: we went to the same high school, Poole Grammar).

The term was chosen to contrast with OLTP or online transaction processing, and was prompted by some clever marketing folks at Essbase, who wanted to promote their multidimensional database product. Codd was famous for his twelve rules defining the relational model and duly came up with twelve rules for analytic systems.

The term was quickly taken up by the rest of the industry, and spawned new definitions (Nigel Pendse’s FASMI test) and multiple variations (MOLAP, HOLAP, ROLAP, Huey, Dewie and Louie, etc.).

Over time, these multiple definitions started muddying the meaning of the term (was it a technology? a user interface? an approach to analysis?), and Gartner decreed that it was ‘just’ part of a larger market called business intelligence. The result has been a long slow decline of the use of the term OLAP, as the Google Trends chart below indicates.

image

Only Nigel Pendse of the OLAP Report tried to side-step this trend, and continued producing OLAP-specific analysis for many years, but “business intelligence” was clearly the mainstream industry term. A few years ago, Nigel sold the OLAP Report to the German BARC group, who initially continued under the same name, and tried vainly to convince everybody that OLAP was still a “hip term,” but finally succumbed to the inevitable and announced last month that they would be changing the name of the report/site to The BI Verdict.

(Sadly, at some point in this process, BARC decided to lock one of Nigel’s best articles — “How not to buy a BI product” – behind their subscription firewall. All I can find on the web is a far-less-entertaining summary of the main points here.)

Since BARC were the last group using the term with any frequency, it’s now fairly safe to say that OLAP’s days are over, but interestingly, the group seems to have chosen to shift to the wrong term. The chart below shows that the search trend for “business intelligence” has been slowly drifting down over the last five years.

image

And the decline is even more pronounced for another standard industry term, “performance management”:

image

Since BI and performance management remain fast-growing markets, this trend is a little surprising – until you look at the search figures for the term analytics. Starting in 2005 (perhaps prompted by the introduction of Google Analytics?), the term has skyrocketed in use.

image

Possible reasons for this may include:

  • Popular books and articles aimed as business people tend to use the term, such as Thomas Davenport’s 1997 book “Competing on Analytics.” This is perhaps because there’s more ambiguity for a business audience, who associate the term “business intelligence” with industry data vendors like Reuters and Thomson (now both part of the same company).
  • The acquisition of the mainstream BI vendors by larger organizations (Hyperion by Oracle, Cognos by IBM, and BusinessObjects by SAP) has meant that the industry has been increasingly using other, more generic terms, such as “embedded analytics” and “analytic applications” to explain the same functionality. And the largest remaining independent vendor, SAS, has proclaimed themselves the leader in “business analytics”

My conclusion? By the time you read this, this blog might well be called “Analytic Questions” instead of “BI Questions”…

[Post to Twitter] Was this interesting? Share with others on Twitter with automatic URL shortening! 

TAGGED:analyticsbusiness intellgencenigel pendseolapperformance managementted codd
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI role in medical industry
The Role Of AI In Transforming Medical Manufacturing
Artificial Intelligence Exclusive
b2b sales
Unseen Barriers: Identifying Bottlenecks In B2B Sales
Business Rules Exclusive Infographic
data intelligence in healthcare
How Data Is Powering Real-Time Intelligence in Health Systems
Big Data Exclusive
intersection of data
The Intersection of Data and Empathy in Modern Support Careers
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Image
Business IntelligenceData MiningExclusiveInside CompaniesMarketingPredictive Analytics

We’re Not Artists: The Craft of Influencing Decision Makers

6 Min Read

Platfora and the Foundation of Business Intelligence for Big Data

7 Min Read

Data Visualizations: The Tip of the Iceberg of Understanding

0 Min Read

Building an Analytical Portal to Support Analytical Culture

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 is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots

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?