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
    image fx (60)
    Data Analytics Driving the Modern E-commerce Warehouse
    13 Min Read
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 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
SHARE

Data Analytics and Dirty Data photo (uncategorized)How much of what your company knows is useful? Which data is current?

Data Analytics and Dirty Data photo (uncategorized)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).

More Read

The World’s 7 Most Powerful Data Scientists
Finding the Right Sponsor for Your Big Data Project
Business Intelligence’s Benefits Suit All Types of Companies
Data Collaboration: Crowdsourcing for Health Care
Saying Goodbye

“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.

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

Why the AI Race Is Being Decided at the Dataset Level
Why the AI Race Is Being Decided at the Dataset Level
Artificial Intelligence Big Data Exclusive
image fx (60)
Data Analytics Driving the Modern E-commerce Warehouse
Analytics Big Data Exclusive
ai for building crypto banks
Building Your Own Crypto Bank with AI
Blockchain Exclusive
julia taubitz vn5s g5spky unsplash
Benefits of AI in Nursing Education Amid Medicaid Cuts
Artificial Intelligence Exclusive News

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

data protection strategies
Data Management

What Are the Best Methods To Keep Online Data Safe?

8 Min Read

Self-Service BI & Adapting Line of Business (LoB) Executives

6 Min Read

Google+, Does it have Potential for Business Use?

9 Min Read

Beyond Hadoop – Completing the Big Data Picture

2 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 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.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?