5 Tips for Improving Data Quality with Low-Code Solutions

Low-code platforms have risen in popularity in recent years. Many have the ability to connect and analyse data from multiple sources, and are becoming the go to tool for managing data quality.

7 minutes read | by Lee Smith | 7 February 2023

Low-code platforms have risen in popularity in recent years. Many of them have the ability to connect and analyse data from multiple sources, and are becoming the go to tool for managing data and improving data quality.

These low-code solutions allow businesses to quickly configure and deploy applications and automated business processes without writing extensive amounts of code. Most low-code platforms feature pre-built templates, drag-and-drop interfaces, and other features making it easier for non-technical users to create and customize their own applications.

One key benefit that some low-code platforms offer is the ability to improve data quality. This is achieved by automating data cleansing and validation processes, creating dashboards to monitor data quality in real-time, implementing data governance workflows, and bringing together data from multiple sources. Low-code can help businesses ensure that their data is accurate, consistent, and accessible – at pace and scale

To get you started we have uncovered five top tips on how to utilise low-code applications to increase efficiency and aid decision making through higher quality data. Let’s dive in.


Tip #1: Use low-code tools to automate data cleansing and validation processes

Data cleansing and data validation are essential processes for ensuring data quality. Data cleansing involves removing or correcting invalid, incomplete, or duplicated data, whereas data validation involves checking data for accuracy and completeness. Automating these processes will help reduce the time and effort required to improve the accuracy and consistency of the data – and that’s where low-code platforms come in.

Low-code platforms make it easier to automate data cleansing and validation processes by allowing business teams, comprised of technical and non-technical users, to build reusable templates and business rules in a simple to use drag-and-drop interface. For example, a process that has been created to remove duplicates from a specific data source can be re-used for another data source.  Simply select the fields in your new data source along with  the criteria for identifying duplicates. Once set-up the application can now be configured to automatically remove the duplicates, saving time and reducing the risk of manual errors.

There are other data cleansing and validation task that low-code platforms can help with such as standardising formats, checking for errors, and filling in missing values. Users can create, or select from a library of re-useable components to perform repetitive tasks. For example, there may be a component for standardising phone numbers, which can be used to ensure that all phone numbers in a database are formatted consistently. This is especially useful when working with data from multiple sources to resolve discrepancies in formatting.


Tip #2: Utilise low-code to build dashboards that visualise and monitor data quality

Using dashboards is a great way to quickly monitor your data quality and helps to quickly identify any potential issues. By visualising your data in interactive charts and graphs allow users to see trends and patterns from the data and spot any anomalies or problems. Ultimately, this helps to speed up the identification of problems allowing the business to adapt quickly to resolve them.

Low-code platforms, like PhixFlow, make it easy for users to create interactive dashboards with data visualisation and real-time updates. Drag-and-drop screen building allows users to select from a library of charting components to display their data in a variety of formats, such as line graphs, bar charts, or pie charts. These dashboards can also be set up to update automatically as new data is added, so that latest data quality metrics can be seen in real-time.

In addition to helping organisations identify data quality issues, dashboards can also be used to track the progress of the data quality improvement efforts and provide the interactivity required to drill-down into more detail. Where any anomalies are identified that haven’t been accommodated into the business rules can then be manually updated.


Tip #3: Create automated workflows that apply consistent data quality  standards and comply with governance policies

Data governance is the set of policies, processes, and systems that organisations use to ensure that their data is accurate, consistent, and compliant with legal and regulatory requirements. By monitoring data governance with automated workflows, organisations can ensure that their data meets specific standards and policies, which helps improve data quality and reduce risk.

Low-code platforms are the ideal tool for creating data governance workflows to enforce standards and policies. Workflows can be customised to specify the data elements that need to be defined, the standards that need to be followed, and the approval process for making changes.

In addition to managing data definitions and metadata, low-code tools can also be used to manage access controls and other data governance-related tasks. For example, the application designer can specify which users can access specific data sets and what actions they can perform on them. Low-code data governance controls ensure that the data consistently meets the designated standards and is managed in a controlled and compliant manner.


Tip #4: Leverage low-code integrations to bring together data from multiple sources

Working with data from multiple sources is challenging. The more systems and data sources involved results in discrepancies and inconsistencies that affect data quality. With the right controls, bringing together data from various sources and integrating it into a low-code platform allows businesses to improve the accuracy and consistency of their data.

Integrating data from various sources is a key strength of many low-code platforms. Most will have templated connections to read and write data from many of the well-known business systems and databases. Once integrated, the data collector can be customised to specify the data elements that need to be consolidated and the mapping between them. After testing the connection and the mappings between the data the integration can then be automated, ensuring the accurate and consistent flow of data.

In addition to improving data accuracy and consistency, low-code platforms also increase efficiency and allow working with a wider range of data. For example, by using a low-code tool to integrate data from a CRM system and a marketing automation system, an organization can gain a more complete view of their customers and target their marketing efforts more effectively.


Tip #5: Incorporate Low-Code into Your Data Governance Framework

Low-code solutions are known for their ease of use, speed, and flexibility, making them an excellent choice for incorporating into your data governance framework. By doing so, you can build a robust data quality assurance process that helps to establish a positive data-focused culture within your organization.

The automation of data validation and standardisation processes, as well as enforcing data quality rules and standards, with low-code applications provides the maintenance of consistent data quality. This reduces human error and ensures that data is used in a manner that is consistent with your goals and objectives.

Consistently high data quality will also help to promote a positive data-focused culture within your business. This is largely due to the enhanced visibility of data throughout the business. Low-code applications also provide the ability for employees to easily make changes to business rules and workflows, meaning that they have control and ownership of the data that matters to them.



Businesses using low-code platforms to automate manual processes will see improved data quality and efficiency throughout the organisation. Improved data quality also drive value by aiding important business decision making. This is achieved through a clearer understanding from more accurate data.

Low-code solutions offer a number of benefits for data management, including increased efficiency, cost savings, and faster time to market. By implementing low-code solutions, organizations will also drive business value through better decision making and improved operational performance.

For more information on how the PhixFlow low-code platform can help you connect, manage and analyse your data, and automate business processes request a demo today.