Data Quality Management Solutions

High-quality data drives better business decisions

Whether your business is a small start-up using spreadsheets to manage and report on data, or a large well-established corporation that has invested heavily in data storage and presentation technologies, data quality management solutions are essential. You need good quality, trustworthy data to provide information about customers, products and services and to inform strategic decision making.

Here at Prokope, we understand that not all the data across your organisation needs to be high quality – achieving this will entail unnecessary effort and investment. We have developed methods and techniques, with the expertise of data quality management consultants, to ensure investment in the continuous improvement of data quality is only focused on data that is key to your organisation.

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How do you achieve high-quality data management?

We are experienced in working with many different organisations across various industries. Prokope’s consultants work collaboratively with our clients to define business rules that, when applied to data, measure the quality of the data across the required set of data quality dimensions. Our data visualisation solutions, incorporating best practices for successful data management, provide rich data quality dashboards that deliver insights and information to key areas of the business. This enables your organisation to identify, understand, and resolve data quality issues effectively.

Data quality management is the key input to any Data Governance organisation. Our Data Quality and Governance framework accelerates, and is at the heart of, all our data quality engagements. This provides our clients with the foundations they need to understand the impact of poor data quality, and everything that is required for the continuous improvement of the quality of data that is key to the organisation.

Prokope's Data Quality Management Services

Ask the Data Quality Management Experts

Our Data Quality consultancy team can manage all your Data Quality Management challenges.

The importance of Data Quality Management Consultants

Effective Data Quality Management, including increasing data accuracy, helps you make data-driven decisions that you can trust.

We will help you to improve and monitor the health and value of your data, giving you the confidence to drive operations, compliance and analytics initiatives.

CASE STUDY

Data Assurance for a leading UK bank

Prokope-led Data Assurance enabled a leading UK financial institution to deliver multiple customer Redress and Remediation projects with confidence.

Data Assurance for a leading UK bank

What is Data Quality Management?

Data Quality Management is crucial for ensuring that the data used for analysis and decision-making is accurate and reliable. By working with a data quality consultant, organisations can implement processes and technologies that improve the health of their data. Effective data quality solutions provide valuable insights, enabling better decision-making and more efficient operations.

Why is Data Quality Management Solutions so important?

Effective Data Quality Management is essential for making sense of your data and ultimately increasing profitability. Outdated or unreliable data can lead to costly mistakes. Engaging with the right data quality consultant establishes a solid foundation across your organisation, ensuring consistent enforcement of data quality standards. This proactive approach helps maintain accurate and reliable data, driving better business outcomes.

Are there real-world examples of Data Quality Management?

Real-time data quality management is critical when a bank processes a customer’s credit card transaction, as it could detect fraudulent purchases. However, updating a loyalty card for the same customer may not require the same urgency. In both scenarios, applying the principles of data quality management solutions efficiently is essential. Engaging with expert data quality consultants ensures that your organisation maintains high standards of data accuracy and reliability, tailored to the specific needs of each process.