What is data quality? Part 3

How do we ensure our data quality?

This is an ever-present point of discussion in many companies, regardless of department or duties. The quality of your data can be evaluated based on many variables, we have already reviewed correct and complete data.

• Accessible
• Relevant
• Comparable
• Valid
• Accuracy
• Completeness
• Reliablity
• Consistency
• Current

Based on these, we will recommend a selection of activities, both manual and system-driven, that can help you evaluate and improve your data quality.

Reliable data

In many cases, having access to reliable data is crucial for the company. If employees and decision-makers do not trust the information that is in the business's system, they stop using the information that is available and that has often been collected over a long period of time. The lack of trust can also lead to several sources of error in the form of own analyzes being carried out alongside the tools that are already in place, in Excel for example. A contributing cause of lack of reliability may be that processes to secure the data are missing or need to be evaluated.

Consistent data

Another parameter for determining data quality is data consistency. If the business is dependent on several data sources, deviations often arise, for example different units, currencies or that dates have different formats, which makes it difficult to consolidate the information between the systems.

Consolidate and Standardize data points

Using a data warehouse solution to collect all data in one place is a good start, but you also need to introduce automatic checks that all data quality parameters are also met, preferably automatically with the help of smart solutions like DataCheck.

Identify keys

Find similarities and patterns in data points that are comparable and allow them to be combined with other data, such as combining order numbers with item numbers and invoice/payment documents to see sales patterns or purchase quantities for individual products.

Summary

Striving for good data quality must be a basis in the work processes that are data-intensive. Use tools for automatic checks of the data points that are important to the business, for example: amounts, dates and currency conversion.

How much do you trust your own data? Do you have the tools you need to visualize and analyze your business?

Are you curious to learn how Business Cloud iPaaS can help your company with integrations and data quality? Contact me below or book a demo and I'll tell you more.

Staffan Hedbrandh, CEO