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What Should Be Included In A Data Quality Checklist Template?

What Should Be Included In A Data Quality Checklist Template?

Data management is an integral part of maintaining business operations. Yet, only 3% of the organizations meet the quality standards!

It is why businesses try to implement a data quality checklist for proper management.

So, have you been trying to find a way to mend the gap existing between your data quality and management? This is where a data quality checklist comes in!

This blog will take you through all the prerequisites of an effective data quality checklist. Furthermore, you will have proper frameworks to help make your B2B data reliable, efficient, and accurate.

Insight into Data Quality

Data Quality Insights

Did you know that about 70% of revenue leaders consider data quality management to be of utmost importance? They debate that a thorough quality test of data will reveal the core of all flawed instances. However, to determine that, a business needs first to understand its problem.

Colleen Graham rightly remarked,

Data quality requires a certain level of sophistication within a company even to understand that it is a problem.”

Data itself is a vast avenue that seems to have no limit. It can either be positive (usable) or negative (unusable)!

In essence, data quality can be determined by its level of accuracy and effectiveness—whether high-quality or low-quality.

So, data quality alludes to either the error-free and unique version of it or the flawed one. A high-quality data has a framework of unique and accurate information.

That being said, high-quality data is credible, comprehensive, carefully chosen, clean, complete, and calculable. On the other hand, low-quality data is flawed and obsolete.

Having poor data quality can subject your business to a loss of 20% revenue! On top of that, it is highly plausible that your lead database has 40% of inaccurate data.

It is why management of data quality is crucial when it comes to retaining customers and generating ROI.

The Meaning of High-Quality Data

Characteristics Of Data Quality

High-quality data generally means that:

  • It has a perfect formatting
  • There is no structure issue
  • It is error-free and complete
  • It has a high accuracy rate
  • Businesses can rely on it
  • It is not obsolete but timeless
  • There is a unique content
  • It is comprehensive and concentrated

On the other hand, insufficient data will make all your business decisions flawed by providing inaccurate insights. Pursuing marketing campaigns with inaccurate data might hamper your ROI. Moreover, these data fields will deteriorate the efficiency and credibility of your organization.

Your business will be affected and will endanger your growth if your marketing data is obsolete. That is where a data quality checklist comes in!

It will help your business harness high-quality data and manage every negative aspect related to it.

Data Quality Checklist Template—Manage Your Business Data Quality Easily

Data Quality Dashboard

Companies across various industries use the data quality checklist as a tool to reduce errors. Do you want to understand how to create a checklist? Take a look at this template and understand what needs to be included:

The Basic Checks On Data

It includes all the recurring tasks upon the renewal of data. So, you need to consider:

  • The verification of formatting
  • Confirming the validity of the data
  • Comparison of data to determine changes
  • Identifying invalid values in the data
  • Spot checking

Performing these tasks will ensure the reduction of inaccuracies in your B2B data. Moreover, you need to review these tasks thoroughly before moving ahead to the advanced checks.

The Advanced Checks On Data

The next step on your data quality checklist should be the process of reviewing and submitting. The tasks that you need to complete during the approval and review process are:

  • The data should be real and accurate
  • Fixing of all red flags before approval
  • Identification of errors before submission
  • Compatibility check between the original document and the final report
  • Determining whether or not knowledgeable people wrote the information

Extra Checks to Determine Legitimacy

Once you have completed these fact-checks and holistically analyzed the data, you can determine the course of action. However, before you can finalize it, there are more aspects to consider:

  • Consistent checking of that data to ensure the fulfillment of all record requirements
  • Assurance of intentional blank information without omission
  • Complete information in all fields
  • Inquiry about the submission of any hard copy of the data (and added)
  • Intricate mention of the entire timeline of the reported data
  • Re-check if the timestamp is accurate to ensure its credibility
  • Cross-checked for the consistency of this data

The data you are submitting should invariably have all the relevant information throughout your organization. Moreover, this data quality checklist template is crucial for the correct submission of your B2B data.

It helps generate ROI by retaining the right prospects and maintain a positive relationship.

The next step in maintaining high quality in your data is integrating data quality control and data profiling. Consequently, you will need to do this at regular intervals and fix all the enables of those previously found errors.

With this data quality checklist template, you are sure to reduce mistakes in your business data.

Summing Up

Now that you know the importance of a data quality checklist, you can implement it in your business. Using this will give you access to accurate data that you can harness to generate ROI. Moreover, without an effective data quality checklist, your company will lose money due to irrelevant marketing.

You can take into account all the insight you received from this blog. Consequently, ensuring that no data in your warehouse is obsolete.

It will help you manage your business’s data quality so that there are no dominant errors. Furthermore, you can use the checklist to perform advanced checks and meet all your objectives.

With this data quality checklist, you can reap huge benefits in your B2B endeavors!

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InfoCleanse (Sam Wilson)