10 Roadblocks to Becoming a Data-Driven Enterprise - InformationWeek

InformationWeek is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them.Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

CIO Insights & Innovation
Security & Risk Strategy
Team Building & Staffing
IT Strategy
Digital Business
Project Management
Programming Languages
Dr. Dobb's
Enterprise Applications
Operating Systems
Productivity/Collaboration Apps
Network Security
Careers & People
Threat Intelligence
IoT
Attacks & Breaches
Application Security
Cloud Security
Endpoint Security
Mobile Security
Perimeter Security
Risk Management
Operations Security
Analytics
Vulnerabilities & Threats
Security & Risk Strategy
Infrastructure as a Service
Platform as a Service
Software as a Service
Cloud Storage
Data Centers
Mobile Applications
Mobile Devices
Mobile Business
Enterprise Mobility Management
AI/Machine Learning
Big Data Analytics
Hardware/Architectures
Software Platforms
IoT
Networking
Wireless Infrastructure
Data Centers
Cloud Infrastructure
Careers and Certifications
Network Security
Government
Healthcare
Wall Street & Technology
Bank Systems & Technology
Insurance & Technology
Industries
Government
Healthcare
Wall Street & Technology
Bank Systems & Technology
Insurance & Technology
IT Life
Careers
Mobile
Mobile Applications
Mobile Devices
Mobile Business
Enterprise Mobility Management
Software
Enterprise Applications
Operating Systems
Productivity/Collaboration Apps
IT Leadership // Digital Business
News
9/4/2018
09:00 AM
Cynthia Harvey
Cynthia Harvey
Slideshows
Connect Directly
Twitter
RSS
E-Mail
0 comments
Comment Now
50%
50%

10 Roadblocks to Becoming a Data-Driven Enterprise

Nearly 100% of enterprises want to become more data-driven, but less than a third have accomplished that goal. A new survey sheds light on the reasons why.
Previous
11 of 11
Next

10. Improperly Labelled Data


A similar problem is data that gets labelled incorrectly. Overall, 37% of respondents said that mislabeled data was a problem, and in this case, it was the IT decision-makers with the most concern, as 40% of them cited the issue in response to the question about the challenges of accessing data.

Again, technology might help data get more appropriate tags, but training might also be necessary to help curb the problem.

In general, if enterprises want to overcome the roadblocks to being more data-driven, they’ll probably need to address all three aspects that contribute to the problems — people, processes and technology.

Image source: Pixabay

Cynthia Harvey is a freelance writer and editor based in the Detroit area. She has been covering the technology industry for more than fifteen years. View Full Bio

We welcome your comments on this topic on our social media channels, or [contact us directly] with questions about the site.
Previous
11 of 11
Next
Comment  | 
Print  | 
More Insights
Webcasts
More Webcasts
White Papers
More White Papers
Reports
More Reports
Editors' Choice
Slideshows
9 Steps Toward Ethical AI
Cynthia Harvey, Freelance Journalist, InformationWeek,  5/15/2019
Commentary
How to Assess Digital Transformation Efforts
Lisa Morgan, Freelance Writer,  5/14/2019
Commentary
Is AutoML the Answer to the Data Science Skills Shortage?
Guest Commentary, Guest Commentary,  5/10/2019
White Papers
Register for InformationWeek Newsletters
Video
Current Issue
A New World of IT Management in 2019
This IT Trend Report highlights how several years of developments in technology and business strategies have led to a subsequent wave of changes in the role of an IT organization, how CIOs and other IT leaders approach management, in addition to the jobs of many IT professionals up and down the org chart.
Download This Issue!
Slideshows
Flash Poll