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: New to Data Quality Analysis Try These “9+1 Things To Do”!
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Warehousing > New to Data Quality Analysis Try These “9+1 Things To Do”!
Data Warehousing

New to Data Quality Analysis Try These “9+1 Things To Do”!

DataQualityEdge
DataQualityEdge
5 Min Read
SHARE

Did you just get moved over from one data warehouse support group to another? Do you know nothing or very little about the data in your new data warehouse? Or are you new to data quality analysis and want to get started on some solid footing?

The following post by Sylvia Moestl Vasilik “9 things to do when you inherit a database” at SQLServerCentral.com is an excellent article for anyone jumping into a new database environment, regardless of the environment or vendor, or the type of database (relational or columnar), Sylvia’s 9 things to do can be applied anywhere.

Building on those “9 things,”if you are less technical and more into data quality analysis or into a data steward role, I recommend adding a 10th thing to do… begin and complete a data profile.

A solid data profile will provide you with a wealth of information and more. A solid data profile will provide you with some interesting insight into the data. Here are a few items that you should be able to capture with a good data profile project.

More Read

Overcoming Data Management Challenges in Online Channel
Help Change the World with Data Science
“Smarter healthcare is intelligent, applying advanced analytics to improve research, diagnosis and…”
Smarter healthcare is instrumented, so our health systems can…
Sustaining Cultural Change
  • You will gain an understanding of the completeness of the data, you’ll see what’s missing and you can begin to ask the questions to the business users why are we missing …


Did you just get moved over from one data warehouse support group to another? Do you know nothing or very little about the data in your new data warehouse? Or are you new to data quality analysis and want to get started on some solid footing?

The following post by Sylvia Moestl Vasilik “9 things to do when you inherit a database” at SQLServerCentral.com is an excellent article for anyone jumping into a new database environment, regardless of the environment or vendor, or the type of database (relational or columnar), Sylvia’s 9 things to do can be applied anywhere.

Building on those “9 things,”if you are less technical and more into data quality analysis or into a data steward role, I recommend adding a 10th thing to do… begin and complete a data profile.

A solid data profile will provide you with a wealth of information and more. A solid data profile will provide you with some interesting insight into the data. Here are a few items that you should be able to capture with a good data profile project.

  • You will gain an understanding of the completeness of the data, you’ll see what’s missing and you can begin to ask the questions to the business users why are we missing this component of the data set(s).
  • How accurate is the data, does it meet the initial requirements or not. How often does a job fail because of bad data; have you lost customers, revenues or received fines due to bad data? You’ll discover soon enough how inaccurate data affects your organization.
  • How timely is the data? Do you have real-time, near real-time or less timely data. Is your data arriving late, on time or not at all? How long is the data relevant for, this will be important for you, your users and maintaining the environment.

Just remember focus yourself first on the most important data, the highly used data, then you can spread out and tackle the rest of the data warehouse. Make sure you have senior management approval, and are able to prioritize the other 9 things to do along with this one.

Other items you can gather while running a data profile project can be identified from the following post, 5 Non-Quality Items to Consider in Data Profiling.

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (60)
How Finance & BI Teams Choose Accounting Software
Big Data Business Intelligence Exclusive
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

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Grid versus Cloud Computing

3 Min Read

For the first time in history, more people live in cities than…

1 Min Read

“Predictive analytics allows your organization to learn from its collective experience and puts this…”

1 Min Read
Image
AnalyticsBig DataBusiness IntelligenceData MiningData WarehousingInside CompaniesModelingPolicy and GovernancePredictive AnalyticsPrivacySentiment AnalyticsSocial Media AnalyticsText AnalyticsUnstructured DataWeb Analytics

Facebook’s Big Data: Equal Parts Exciting and Terrifying?

8 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?