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: Awesome Analytics: Are We There Yet?
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 > Awesome Analytics: Are We There Yet?
AnalyticsBig Data

Awesome Analytics: Are We There Yet?

Timo Elliott
Timo Elliott
3 Min Read
Awesome Analytics: Are We There Yet?
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

As I prepared for a presentation at the Gartner BI conference in Sydney a couple of weeks ago, I thought I’d take a look at old research to how far we’ve come with Analytics in the last few decades.

At first glance, the answers is ‘not very far.’

For example, in 1997, only 12% of executives reported basing their decisions on hard facts. By 2014, that had dropped to just 10%.

As I prepared for a presentation at the Gartner BI conference in Sydney a couple of weeks ago, I thought I’d take a look at old research to how far we’ve come with Analytics in the last few decades.

More Read

What Changes Will Big Data Analytics Bring?
What Changes Will Big Data Analytics Bring?
Public vs. Private vs. Hybrid Cloud – Exploring the use Cases
3 Remarkable Big Data Platforms for Web Development
Data = Opportunity: But Are You Monetizing Information?
Apache Spark Use Cases

At first glance, the answers is ‘not very far.’

For example, in 1997, only 12% of executives reported basing their decisions on hard facts. By 2014, that had dropped to just 10%.

analytics now and then -- gut rules2

Despite decades of BI investment, executive reliance on gut feel has actually increased.
(Why the worst-practice 3D shaded pie-charts? Just to troll the data viz purists 🙂 ).

A hot topic of Gartner BI research in the late 1990s was the increasingly large ‘fact gap,’ whereby the amount of data available for decisions was rapidly outstripping the available analytic resources.

With some minor modifications, such as changing ‘Terabytes’ to ‘Petabyes’ and ‘Analytic Personnel’ to ‘Data Scientists,’ the picture looks remarkably similar twenty years later.

fact gap update

An update to Gartner research from 1996. Plus ça change…

It’s hard to compare perfectly, because of different research methodologies used over the years, but it also seems that the largest factors holding back successful Business Intelligence also haven’t changed very much.

The top three problems remain data quality, ease of use, and the difficulty of integrating different systems.

biggest barriers to business intelligence

The top three barriers to business intelligence have remained largely unchanged for over a decade

The reality is that today’s technology is much more powerful and widely used than in the past — but what was hard then remains hard today.

what's still not awesome

What if we could take all of today’s technologies, and start again from scratch? That ended up being the theme of my presentation, and the subject of future posts. In the meantime, please find the presentation below — note that you can download the .pptx version by clicking the right-hand button and going to the slideshare site.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article's core relationship is workload-by-workload decision-making for cloud migration, where s
Which Workloads Should Move to the Cloud?
Cloud Computing Exclusive IT
Flat editorial illustration: The article positions data governance as a strategic board-level concern rather than a purely techni
Why Data Governance Is Becoming a Board-Level Business Priority
Big Data Exclusive Policy and Governance
Flat editorial illustration: The article argues that data annotation quality should be measured by inspectable gold sets, written
The Top Data Annotation Companies Are Separated by Proof of Quality, Not Headcount
Big Data Exclusive
Flat editorial illustration: The article's core relationship is the gap between raw bank-feed records and reliable subscription i
Subscription Trackers Have a Transaction Data Problem
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

The Global Nature of Big Data and Analytics
AnalyticsBig DataBusiness IntelligenceCollaborative Data

The Global Nature of Big Data and Analytics

5 Min Read
What If We Could Feel the Big Data Sugar Rush Faster?
Big DataData ManagementData MiningData QualityData VisualizationData WarehousingKnowledge ManagementSocial DataUnstructured DataWorkforce Data

What If We Could Feel the Big Data Sugar Rush Faster?

5 Min Read
Scary Big Data, Cool 3D Analytics and More
Analytics

Scary Big Data, Cool 3D Analytics and More

6 Min Read
Data Analysts, Data Scientists, and the Rest of Us
AnalyticsCulture/Leadership

Data Analysts, Data Scientists, and the Rest of Us

6 Min Read

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

5 Great Tips for Using Data Analytics for Website UX
5 Great Tips for Using Data Analytics for Website UX
Big Data
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence 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?