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: How “Dirty Data” Derails Your Company’s Data Analytics and ROI
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 > How “Dirty Data” Derails Your Company’s Data Analytics and ROI
Best PracticesData QualityUnstructured Data

How “Dirty Data” Derails Your Company’s Data Analytics and ROI

Brett Stupakevich
Brett Stupakevich
3 Min Read
How “Dirty Data” Derails Your Company’s Data Analytics and ROI
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

How much of what your company knows is useful? Which data is current? In a recent webinar about the dangers of “Dirty Data” Jay Hidalgo of The Annuitas Group says many companies simply don’t know. He estimated that 30 percent of companies have no strategy for “data hygiene” – removing duplicates or obsolete information. He said 34 percent of companies ask the front-end sales team to update customer and prospect files but even that can be flawed among multi-product or different “views” of the same company, client or transaction.

For sales and marketing especially any data analytics and business intelligence based on “bad data” will yield misleading or incorrect results. In fact, 8 of 10 companies indicated that dirty data is hindering their lead generation campaigns. Instead of cleaning and clarifying, companies pile ever increasing data into storage with a “we’ll sort it all out later” approach, particularly sales and marketing role companies.  But real-time data changes things: the sheer volume of information and how quickly it makes previous knowledge and data obsolete requires changing habits.

Enter a new support industry to recover, clean and manage that information. Data Service Providers, companies that analyze, double-check and connect the dots when you have partial details and need more. Hoovers and ZoomInfo are two examples for finding business people and companies; ThinkorSwim takes every transaction from financial markets to analyze patterns, trends and activity levels. News aggregators, auction pricing guides and search engines are just a few other examples of meta-data (data ABOUT your data).

“The problem of data decay is that it’s faster than it’s ever been. Seventy one percent of business cards you collect have at least one change within 12 months,” said Sam Zales, president of ZoomInfo. An estimated 600,000 small businesses are created and vaporize in a five-year-period. Knowing which ones can be critical if that is your marketplace.

More Read

Eulogy for a Beloved Market Research Organization
Eulogy for a Beloved Market Research Organization
Climate Change Under the Text Analytics Microscope
Using Analytics to Handicap The Masters Golf Tournament
Data Quality by Example: Data Quality Airlines
The Secret BI / Big Data Playbook

No human-powered research effort could possibly keep pace, so a regular schedule and program is an important first-step. Like a health inspector, you can’t expect to check every restaurant daily – but responding to complaints and maintaining a rigorous plan for oversight is a good policy. Testing data for accuracy on a regular schedule answers questions such as “What do you know? And how do you know?”

Then you can confidently answer the question “Are you sure?”

Subscribe to our blog to stay informed on how to improve your company’s data quality and other data analytics topics.

David Wallace
Spotfire Blogging Team

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Retailers Should Stop Treating Every Stockout as Equal -- AI-generated illustration
Retailers Should Stop Treating Every Stockout as Equal
Business Intelligence Exclusive
Best Vibe Coding Cleanup Specialists in the USA: Fix or Rebuild? -- AI-generated illustration
Best Vibe Coding Cleanup Specialists in the USA: Fix or Rebuild?
Development Exclusive
Using Warehouse, Transportation and Order Data to Plan Distribution-Center Capacity -- AI-generated illustration
Using Warehouse, Transportation and Order Data to Plan Distribution-Center Capacity
Big Data Exclusive
Flat editorial illustration: The article centers on AI budget discipline for 2027 business planning, linking AI spending to measu
10 AI Trends That Should Shape Your 2027 Business Plan
Artificial Intelligence Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

Big Data and Analytics – Suggestions to Approach
AnalyticsBig DataData ManagementUnstructured Data

Big Data and Analytics – Suggestions to Approach

4 Min Read
Collaborative Analytics and the Benefits of Local Language Support
Best PracticesCollaborative Data

Collaborative Analytics and the Benefits of Local Language Support

3 Min Read
Obsolescence and the ERP system: When the writing is on the wall
Business IntelligenceData Quality

Obsolescence and the ERP system: When the writing is on the wall

6 Min Read
The Butterfly Effect and Data Quality
CRMData QualityData Warehousing

The Butterfly Effect and Data Quality

4 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 chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
ai chatbot
How AI Website Chatbots Improve Customer Support and Lead Generation
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?