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: How to Define Big Data
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > How to Define Big Data
Uncategorized

How to Define Big Data

Brett Stupakevich
Brett Stupakevich
3 Min Read
SHARE

Lumiere et optique photo (information management big data )“Big data” is a popular term these days – it seems to pop up everywhere. But do people mean the same thing when they say those words?

Lumiere et optique photo (information management big data )“Big data” is a popular term these days – it seems to pop up everywhere. But do people mean the same thing when they say those words?

In The Big Data Management Challenge, a recent report from Information Week, Michael Biddick provides a very useful description of what constitutes big data. He suggests there are four elements needed for data to qualify as “big.”

More Read

Why Learn R? It’s the language of Statistics
Recommended read: Seizing the White Space
The lesson of the Palace of Culture and Science
NYT article on IBM’s Jeopardy-playing computer
4 Retail BI Lessons to Learn from Google’s Nexus Fail
  • The most obvious is size. A good point of demarcation is around 30 terabytes.
  • Next is type. Structured data can be easy to work with even in very large amounts, whereas multiple data types (for example, structured, unstructured, plus semi-structured) can be challenging even when data sets are smaller.
  • One of the most challenging elements is latency. “Really big” data typically changes fast.
  • Finally, there’s complexity. Complex data may involve sparseness, inconsistency, and other atypical qualities.

Recognizing big data is the first step to managing it successfully – and the second step is establishing a management strategy specifically designed for big data.

But according to the Information Week survey (drawing on 231 IT professionals from organizations with 10 terabytes or more of data), only 33% of respondents could answer “yes” to this question: Does your organization distinguish “data” from “big data,” using distinct tools and management approaches for higher volume, complexity and dynamic data processing?” Fifty-six percent of respondents say “no,” and 11% admit they don’t know.

From that perspective, it’s no surprise to find that only 6% of the survey participants say there were “no barriers” to the successful management of big data at their organizations.

The highest percentage identify “budget constraints” as a major barrier, but many also cite problems of limited awareness and capability within their organizations. “Lack of knowledge of big data tool implementation” is cited by 44% of respondents, “cost and availability of training” by 41%, and “lack of expertise or experience” by 34%.

Perhaps the most interesting insight can be derived from the way the respondents rate their own understanding of big data tools and strategies.

The 231 professionals range from IT director/manager level (33%) and IT/IS staff (38%) to IT execs (9%) as well as a few business executives, non-IT managers, and consultants. Only 8%, however, say they have “ample knowledge” of technologies specifically designed to manage the needs of big data. Most of the survey participants – 63% – describe themselves as “somewhat familiar” with big data technologies, while 25% are “not very familiar.”

All in all, it seems there’s plenty of room in most companies for improvements in the understanding of big data and the implementation of appropriate management strategies.


 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Edge Computing in IoT
Unique Capabilities of Edge Computing in IoT
Exclusive Internet of Things
Turning Geographic Data Into Competitive Advantage
The Rise of Location Intelligence: Turning Geographic Data Into Competitive Advantage
Big Data Exclusive
AI Recruitment Software Solution
The Best AI Recruitment Software Solution: Transforming Hiring with Smarter Tech
Artificial Intelligence Exclusive
real estate data
How Big Data Is Changes How We Buy and Sell Real Estate
Big Data Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Adaptive Insights Highlights Importance of Strategic Finance

10 Min Read

Really Bad Stuff About Social Media

5 Min Read

IT Budget Hacking (w$$t)

7 Min Read

So you think you can run a search conference…

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 chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
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.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?