💠Data Quality: Definition and FAQs | XS’ Issue #22
Defining Your Data Quality
In order to make smart business decisions, you need accurate and high-quality data. But what is data quality, exactly? And how can you ensure your data is of the highest quality?
Today, we'll answer those questions and more. We'll also discuss some tips for improving the quality of your data. So read on for all the details!
What Is Data Quality?
Data quality is the measure of how well suited a data set is to serve its specific purpose. Measures of data quality are based on data quality characteristics such as accuracy, completeness, consistency, validity, uniqueness, and timeliness.
For example, data that is accurate and complete can be used to make sound business decisions, while data that is inaccurate or incomplete can lead to costly errors. Data quality is, therefore, essential for businesses that rely on data-driven decision-making.
There are many factors that can impact the quality of data:
What Are the Dimensions of Data Quality?
Accuracy: the data should represent real-world circumstances
Completeness: ability to successfully present all accessible needed values
Consistency: uniformity of data as it moves across networks and applications
Timeliness: data that is available when it is needed
Uniqueness: there are no value duplications or overlaps across all data sets
Validity: data should be collected in the right format and within the right range
How to Improve Data Quality
There are many ways to improve data quality, but some basic methods include:
data standardization
checking for consistency
validating
quality monitoring
matching
Why Is Data Quality Important to an Organization?
Data is the lifeblood of any modern organization, and ensuring its quality is essential to success.
Poor data can lead to bad decision-making, wasted resources, and diminished profits. On the other hand, high-quality data allows organizations to make informed decisions, allocate resources efficiently, and maximize their revenue.
In today's data-driven world, quality data is more important than ever before.
Rounding Up the Stack
Each week, we try to read, listen to, and watch tens of blog posts (if not more than a hundred), guides, podcasts, videos, webinars, and any means of content to deliver you the best content from the last week.
These are the content from last week that we enjoyed reading and that caught our attention:
Blog Posts
Why Your Product Design Needs a Content Model
Many product teams aren’t familiar with content models and their benefits. Does your team know how to use content models to support the evolution of your product design:
Why Your Product Design Needs a Content Model — kontent.ai
It's True: Privacy Regulations Made Personalization Better
Here’s a look at where the B2B industry stands in terms of privacy and personalization, how the two relate to one another — and what it all means for marketers and sellers today:
The Surprising Interplay Between Privacy Restrictions and Better Personalization — www.cmswire.com
Edge, Fog, and Cloud Computing: Where You Process Data Matters
Newer terms, such as fog computing, cloudlets, and the edge, might have you wondering just where that data is going:
Edge, Fog, and Cloud Computing: Where You Process Data Matters — quix.ai
Comparing Customer Data Platforms vs. Marketing Automation For Improving the Customer Experience
Here’s a quick comparative overview of the pros and cons of a customer data platform vs. marketing automation for business users:
Comparing Customer Data Platforms vs. Marketing Automation For Improving the Customer Experience — blog.treasuredata.com
The Rise of Omnichannel Content Platforms
Omnichannel content platforms will likely not replace your existing content management systems—but co-exist with them:
The Rise of Omnichannel Content Platforms — martech.org
BONUS READING: The Buzzwordless Three Tenets of the Jamstack
Podcast Episodes
Marketing, Customer Experience Technology Leadership
Chris O'Brien, VP of Digital Marketing Technology at M&T Bank, caught up with CX Decoded to discuss the challenges of managing the marketing technology stack. He shares his thoughts on how the role of marketing technologists has evolved, how he keeps up with the pace of new technology, and what's coming next:
Marketing, Customer Experience Technology Leadership - CX Decoded By CMSWire — open.spotify.com
Composable Commerce 101 with Deity
In this episode, you’ll listen to a discussion about how it differs from the monolithic approach, how to know if you’re outgrowing your monolith, the fake vs true composable commerce, and so much more.
Composable Commerce 101 with Deity - Lessons for Tomorrow — open.spotify.com
Videos and Webinars
Composable Commerce Connecting The Dots with PBCs
In this video, you’ll learn how to connect the dots on composable commerce:
Guides, Case Studies, and Reports
Vue.js vs. React - How to Choose the Right Framework
In this article, you will read the comparison of two excellent JavaScript frameworks, their pros, and cons, as well as some use cases built with each of them. You’ll also look at how to choose the best one for your next project:
Vue.js vs React - How to Choose the Right Framework — graphcms.com
Upcoming Events and Webinars
Hands On with Contentful and Ninetailed
In this lesson, you’re going to get into a hands-on personalization experience with Ninetailed and Contentful. Throughout the lesson, you'll learn how to set up personalization campaigns within Contentful, create audiences for your campaigns, attach audiences and variants to each other, and many more:
🗓 Thursday, June 16, 2022 @ 7.30 am PDT / 4.30 pm CET
Hands On with Contentful and Ninetailed — www.headlesscreator.com
-
That’s it from our side.
Hope you’ll enjoy the content presented above.
Please let us know if you have any questions, comments, or feedback. Don’t hesitate to reach out to us by replying to one of the emails or emailing directly to me via esat@experiencestack.co
And, if you think your friends or colleagues might enjoy reading this newsletter, feel free to forward it to them 🤗
Till next time 😉