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
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    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
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Defining Analytics: Data, Information and Knowledge
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 > Defining Analytics: Data, Information and Knowledge
Predictive Analytics

Defining Analytics: Data, Information and Knowledge

Steve Bennett
Steve Bennett
5 Min Read
SHARE

Following-up to my blog ‘Just Tell Me What I’m Doing‘, I’m starting a series of posts that define the key concepts and terms that make up my analytic world. Everything I do is coloured by my experience actually doing analytics in commercial organisations. So while I believe these posts will present practical definitions that will be actionable in the business world, I know that there are other worlds in academia and science where they are less relevant. At the very least, people in these areas will gain a better understanding of how business regards analytics.


Bennett’s AnalyticaCortec_black_logo  
   A Practitioner’s Guide To Analytics



Data, Information and Knowledge


Information is a collection of related data – often transformed and aggregated – about a topic. In business, that topic is often insight about…

Following-up to my blog ‘Just Tell Me What I’m Doing‘, I’m starting a series of posts that define the key concepts and terms that make up my analytic world. Everything I do is coloured by my experience actually doing analytics in commercial organisations. So while I believe these posts will present practical definitions that will be actionable in the business world, I know that there are other worlds in academia and science where they are less relevant. At the very least, people in these areas will gain a better understanding of how business regards analytics.


Bennett’s AnalyticaCortec_black_logo  
   A Practitioner’s Guide To Analytics



Data, Information and Knowledge


Information is a collection of related data – often transformed and aggregated – about a topic. In business, that topic is often insight about an operational area or a performance question. In analytics, information is often used interchangeably to mean ‘data’ but data is actually best thought of as something that on its own carries no meaning. The main differences are in the degree of meaning and the level of abstraction being considered. To explain:

Degree Of Meaning

Data, information and knowledge all have some degree of meaning. Even data has meaning at some level. For example:

  • data: 99.9 is a number (you know it is probably not text). There is still a possibility that 99.9 is code for a text string or value. 
  • information: 99.9 is the percent of transactions successfully processed by an application.
  • knowledge: 99.9 is 0.05 below the acceptable level for failed transactions with our customers.

Level Of Abstraction

Data is the lowest level of abstraction, information is the next level, and finally, knowledge is the highest level among all three.

Be careful: abstraction is not the same as summarisation. Summaries may only be the sum of individual pieces of data. This doesn’t change the data into information in and of itself. An example:

A list of amounts 5, 8, 5, 2 can be summed to 20. Is 20 information?

Sources

In the business intelligence world data is extracted from fixed sources (batch or in real time, it doesn’t matter). Sources are usually either transactional applications or reference data. All sources have meaning. Transactional data has meaning because:

  • each transaction is stored in one or more records and this gives context to the individual data items of the record.
  • the source application is known and that is information that gives additional meaning to the data.

Reference data also has meaning as the table(s) within which it is stored has an internal meaning due to the relationship between the table rows. Typically this meaning is either hierarchical (for example an organisational structure or products grouped into categories) or group (for example a list of product codes or currencies).

In order for data to become information, it must be interpreted and take on a meaning.

Analytica Illustration

An example (care of Wikipedia):

“The height of Mt. Everest is generally considered as “data”, a book on Mt. Everest geological characteristics may be considered as “information”, and a report containing practical information on the best way to reach Mt. Everest’s peak may be considered as “knowledge”.”

Related Terms and Concepts

Refer also to Data

Refer also to Metadata


Comments? Via form below or send feedback to
analytica@tbig.com.au
         version 0.1 201002



Link to original post

TAGGED:analyticsmetadata
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI video surveilance
AI Video Surveillance for Safer Businesses
Artificial Intelligence Exclusive
Managed IT Services
Comparing Affordable Managed IT Services for Denver’s Remote Workforce
Exclusive IT
human verification tool for business
Human Verification Tools Help Make Smarter Data-Driven Decisions
Big Data Exclusive
ai in business
Recurring Revenue Strategies for the AI Business Era
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Report: 6th Annual SAS HLS Executive Conference

7 Min Read
using geographic data in analysis
Uncategorized

Using Geographic Data

8 Min Read

Four Trends in Business Intelligence and Data Analytics

6 Min Read
benefits of data lakes
Big DataData LakeExclusive

The Business And Technological Benefits Of Data Lakes

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.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?