Data quality plays a crucial role in the growth of a company. Each business should desire to adopt the best technology available. This is to ensure high-quality data collection. Marketing campaigns use data to target the right audience based on data that is collected and data also influences internal operations. Using this data effectively will ensure company growth over time.
Substandard data quality will result in creating strategies that will negatively affect any return on your investment. In other words, your business can suffer immensely by using incorrect data to analyze overall performance.
What Exactly is Data Quality?
So, let's start with defining what data quality is. High-quality data is a mixture of two components.
First is the accuracy of the data and its comprehensiveness to complete the tasks it was collected for.
Second is in the presentation of this data to the correct audience to use it successfully.
Effects Of Poor Data Quality
- When it comes to marketing, inaccurate data can actually harm your business by sending out the wrong message to prospects or repeating messages that can cause will end up sending the wrong message to your prospects, or you’ll end up sending the same message to the same person again and again, this will definitely affect your reputation.
- In online sales you can use data from previous transactions to predict what future customers will purchase. Without accurate data you’ll end up displaying wrong products to prospects and that means low conversion rates.
- When you are working on supplies, inaccurate data can hurt your supply/demand ratios resulting in a negative balance on either side.
- At the corporate level you’ll face obstacles when it comes to implementing cost reduction programs.
- You won’t be able to recognize market opportunities on time because you’re not ready to repurpose existing data that worked in the past.
How Do You Improve Data Quality?
Increase Data Quality Dimension
If you want to improve the quality of your data you should first improve the dimensions of your data. Uniqueness is the first thing to consider on this aspect. A lot of duplicates can be found throughout data collection. Therefore, there is the need to crosscheck and ensure that no info is displayed multiple times so it’s unique.
Data Quality Management
You have to make sure there is a system in place in order to ensure the continuous supply of accurate data for your company and business; you also need to explore a set of remedies as an effort to prevent data problems in the feature.
This is where you provide a set of policies and standards needing to be addressed for every data element. This can be as simple as establishing rules for your business that must be followed before establishing any data report.
All the data personnel who will be assigned for data quality check-up should be qualified to perform the task at hand. Data profiling is supported using dedicated technology in order to understand all data assets involved for high-quality data management. Frequency and distribution play a key role when it comes to data profiling, they must be addressed consequently.
The Best Practices For Quality
- You should make sure there is top-level management in any data project, with the right management you’re guaranteed with the highest data quality for your business.
- Employ data quality activities as part of the governance for your framework, this should be standards, policies, and roles for each and every of your business glossary.
- You should begin with a root cause analysis for each data error found.
- When you’re looking for solutions to an error you should set up a process and technology which will prevent the problem from happening again.
- Always use automation, we’re living in the digital age and there is the need to automate your data input instead of manually typing it.
In summation, there are a lot of consequences for using incorrect data for your business, when the wrong data is used in your business everything goes wrong. Data quality is a must for any business to succeed long term.