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 (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Days Without A Data Quality Issue
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 > Days Without A Data Quality Issue
Uncategorized

Days Without A Data Quality Issue

JimHarris
JimHarris
8 Min Read
SHARE

In 1970, the United States Department of Labor created the Occupational Safety and Health Administration (OSHA). The mission of OSHA is to prevent work-related injuries, illnesses, and deaths. Based on statistics from 2007, since OSHA’s inception, occupational deaths in the United States have been cut by 62% and workplace injuries have declined by 42%.

Contents
A Culture of Data QualityData Quality AssessmentsData GovernanceDays Without A Data Quality IssueRelated Posts

OSHA regularly conducts inspections to determine if organizations are in compliance with safety standards and assesses financial penalties for violations. In order to both promote workplace safety and avoid penalties, organizations provide their employees with training on the appropriate precautions and procedures to follow in the event of an accident or an emergency.

Training programs certify new employees in safety protocols and indoctrinate them into the culture of a safety-conscious workplace. By requiring periodic re-certification, all employees maintain awareness of their personal responsibility in both avoiding workplace accidents and responding appropriately to emergencies.

Although there has been some debate about the effectiveness of the regulations and the enforcement policies, over the years OSHA has unquestionably .. .. …

More Read

KDD 2009 Panel Report: Open Standards and Cloud Computing
Daniel Tunkelang idealizes Twitter
The Risks of Using One Backup Solution Over Another [VIDEO]
The 3 Components of Digital Business Transformation
3 Ways to Access Your Predictive Analytics in the Cloud



In 1970, the United States Department of Labor created the Occupational Safety and Health Administration (OSHA). The mission of OSHA is to prevent work-related injuries, illnesses, and deaths. Based on statistics from 2007, since OSHA’s inception, occupational deaths in the United States have been cut by 62% and workplace injuries have declined by 42%.

OSHA regularly conducts inspections to determine if organizations are in compliance with safety standards and assesses financial penalties for violations. In order to both promote workplace safety and avoid penalties, organizations provide their employees with training on the appropriate precautions and procedures to follow in the event of an accident or an emergency.

Training programs certify new employees in safety protocols and indoctrinate them into the culture of a safety-conscious workplace. By requiring periodic re-certification, all employees maintain awareness of their personal responsibility in both avoiding workplace accidents and responding appropriately to emergencies.

Although there has been some debate about the effectiveness of the regulations and the enforcement policies, over the years OSHA has unquestionably brought about many necessary changes, especially in the area of industrial work site safety where dangerous machinery and hazardous materials are quite common. 

Obviously, even with well-defined safety standards in place, workplace accidents will still occasionally occur. However, these standards have helped greatly reduce both the frequency and severity of the accidents. And most importantly, safety has become a natural part of the organization’s daily work routine.

A Culture of Data Quality

Similar to indoctrinating employees into the culture of a safety-conscious workplace, more and more organizations are realizing the importance of creating and maintaining the culture of a data quality conscious workplace. A culture of data quality is essential for effective enterprise information management.

Waiting until a serious data quality issue negatively impacts the organization before starting an enterprise data quality program is analogous to waiting until a serious workplace accident occurs before starting a safety program.

Many data quality issues are caused by a lack of data ownership and an absence of clear guidelines indicating who is responsible for ensuring that data is of sufficient quality to meet the daily business needs of the enterprise. In order for data quality to be taken seriously within your organization, everyone first needs to know that data quality is an enterprise-wide priority.

Additionally, data quality standards must be well-defined, and everyone must accept their personal responsibility in both preventing data quality issues and responding appropriately to mitigate the associated business risks when issues do occur.

Data Quality Assessments

The data equivalent of a safety inspection is a data quality assessment, which provides a much needed reality check for the perceptions and assumptions that the enterprise has about the quality of its data. 

Performing a data quality assessment helps with a wide variety of tasks including: verifying data matches the metadata that describes it, preparing meaningful questions for subject matter experts, understanding how data is being used, quantifying the business impacts of poor quality data, and evaluating the ROI of data quality improvements.

An initial assessment provides a baseline and helps establish data quality standards as well as set realistic goals for improvement. Subsequent data quality assessments, which should be performed on a regular basis, will track your overall progress.

Although preventing data quality issues is your ultimate goal, don’t let the pursuit of perfection undermine your efforts. Always be mindful of the data quality issues that remain unresolved, but let them serve as motivation. Learn from your mistakes without focusing on your failures – focus instead on making steady progress toward improving your data quality.

Data Governance

The data equivalent of verifying compliance with safety standards is data governance, which establishes policies and procedures to align people throughout the organization. Enterprise data quality programs require a data governance framework in order successfully deploy data quality as an enterprise-wide initiative. 

By facilitating the collaboration of all business and technical stakeholders, aligning data usage with business metrics, enforcing data ownership, and prioritizing data quality, data governance enables effective enterprise information management.

Obviously, even with well-defined and well-managed data governance policies and procedures in place, data quality issues will still occasionally occur. However, your goal is to greatly reduce both the frequency and severity of your data quality issues. 

And most importantly, the responsibility for ensuring that data is of sufficient quality to meet your daily business needs, has now become a natural part of your organization’s daily work routine.

Days Without A Data Quality Issue

Organizations commonly display a sign indicating how long they have gone without a workplace accident. 

Proving that I certainly did not miss my calling as a graphic designer, I created this “sign” for Days Without A Data Quality Issue:

Days Without A Data Quality Issue

Related Posts

Poor Data Quality is a Virus

DQ-Tip: “Don’t pass bad data on to the next person…”

The Only Thing Necessary for Poor Data Quality

Data Governance and Data Quality

Link to original post

TAGGED:data quality
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Some TLC for Your Data

4 Min Read
Data Scientists
Big DataCollaborative DataData ManagementIT

4 Things Data Scientists Can Learn From SoundCloud’s Process

8 Min Read

Recently Read 02/10/2010

6 Min Read

Top 10 interesting companies in Data Management

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.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

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?