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: When Do You need All the Data for Big 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 > Data Management > Best Practices > When Do You need All the Data for Big Analytics?
AnalyticsBest PracticesData QualityData WarehousingModeling

When Do You need All the Data for Big Analytics?

DavidMSmith
DavidMSmith
2 Min Read
When Do You need All the Data for Big Analytics?
Illustration generated with qwen-image-Q4_K_M + Lightning LoRA (local ComfyUI).
SHARE

In the 2012 edition of the SAP Sybase Capital Markets Guide, Revolution Analytics’ Senior Advisor for Products and Strategy (and former CEO) Norman Nie writes about the “Five Benefits of Big Analytics”. (You can also read his article at Enterprise Innovation.) Norman makes the argument that while sampling and aggregation are often useful ways of handling very large data sets for statistical analysis, there are nonetheless several situations where using all of the data in the analysis is beneficial and/or important. They include situations where you need to:

  1. Make Predictions with Data Mining
  2. Deploy More Powerful Predictive Models
  3. Find and Understand Rare Events
  4. Extract and Analyze “Low-Incidence Populations”
  5. Move Beyond “Statistical Significance”

Not coincidentally, many of the big-data analysis features of Revolution R Enterprise have been designed to support these classes of data analysis. You can read the full article by dowloading the 2012 Sybase Capital Markets Guide from the link below (it’s on pages 16-19). An expanded version of the article is also available as a white paper from Revolution Analytics.

SAP Sybase: Capital Markets Guide 2012

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Flat editorial illustration: The article’s core relationship is a transfer of discipline from regulated laboratories to analytics
What Business Intelligence Teams Can Learn from Lab Data Governance
Business Intelligence Exclusive
Flat editorial illustration: A guaranteed reward can raise participation while skewing the respondent pool toward active customer
Incentive-Driven Response Bias: Auditing Sample Composition Before You Trust Survey Data
Big Data Data Quality Exclusive
Flat editorial illustration: The article’s core relationship is observable blockchain activity becoming a trustworthy business me
Blockchain Dashboards Need Better Definitions, Not More Charts
Blockchain Exclusive
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

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

What You Need to Know About Duqu
Best PracticesSecurity

What You Need to Know About Duqu

6 Min Read
5 Benefits of Analytics to Manage Commercial Construction
Analytics

5 Benefits of Analytics to Manage Commercial Construction

5 Min Read
Will Predictive Analytics Help Forecast Profitable IPOs for Stock Traders?
Predictive Analytics

Will Predictive Analytics Help Forecast Profitable IPOs for Stock Traders?

5 Min Read
What’s the Difference Between Business Intelligence (BI) and EPM?
AnalyticsBig DataBusiness IntelligenceCloud ComputingCRMData ManagementSoftware

What’s the Difference Between Business Intelligence (BI) and EPM?

11 Min Read

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

Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
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?