Data Quality: The Foundation of Informed Decision-Making

In today’s data-driven business landscape, the quality of your data can make or break your organization’s success. As the volume and complexity of data continue to grow exponentially, ensuring data quality has become more critical than ever. Let’s explore why data quality matters and how Actian’s solutions can help you achieve and maintain high-quality data.

Understanding Data Quality Management

Data Quality Management (DQM) is the set of mature processes, tools, and in-depth understanding of data needed to make informed decisions and solve problems while minimizing risk and impact to your organization or customers1. It’s not just about having high-quality data; it’s about using that data effectively to serve your purposes with flexibility and agility.

Join our upcoming webinar and see how Actian is helping to solve data quality challenges. Register now.

The Attributes of Data Quality

To truly understand data quality, we need to consider several key attributes:

• Completeness: Are there any missing fields or information?
• Validity: Does the data match its intended use?
• Uniqueness: Are you relying on the correct set of data without redundancy?
• Consistency: Is the same information available across all concerned parties?
• Timeliness: Does the data represent the most accurate and up-to-date information?
• Accuracy: Are the data values as expected?
• Integrity: Does the data meet your quality governance standards?1

The Impact of Poor Data Quality

The consequences of poor data quality can be severe. Before the COVID-19 pandemic, Gartner estimated that the annual financial impact of poor data quality was around $15 million. This figure has likely increased since then, highlighting the critical need for effective DQM strategies. 

Poor data quality can lead to:

• Lack of trust in data, causing employees to create their own versions.
• Insufficient data underpinning bad decisions.
• Increased costs of data management and storage.
• Lack of uniformity in data use, complicating application usage.
• Unacceptable levels of risk or potential reputational damage.
• Communication and collaboration silos.
• Inability to react to market changes or crises.
• Failure to introduce digital practices that enable cross-departmental data usage.

 Implementing a Data Quality Management Framework

Organizations need a robust DQM framework to address these challenges. This framework should guide your data quality governance policies and processes, providing guardrails and metrics to help staff, IT, and vendors keep your data safe, secure, and usable.

Key considerations when building your framework include:

• Accountability: Who will lead your data strategy and governance?
• Transparency: How will you share data rules and gather feedback?
• Compliance: How will you ensure policies and standards are followed?
• Protection: What measures will you take to secure, backup, and manage your data?

Actian’s Approach to Data Quality

Actian offers powerful solutions to help organizations improve and maintain their data quality. Actian provides a comprehensive suite of data profiling, cleansing, and monitoring tools. 

Data Profiling Made Easy

With Actian, profiling your data is just a click away. The intuitive interface allows you to tailor rules to your unique requirements or leverage expert recommendations to ensure your data is correct and complete. 

Intelligent Data Quality Recommendations

Actian’s advanced algorithms and intelligent pattern recognition examine your data, accurately uncovering potential quality issues. You can create tailored rules or rely on Actian’s expert recommendations to process your data and isolate elements that don’t meet specified criteria.

Continuous Data Quality Monitoring

Actian enables you to automate and scale data profiling across datasets of any size or complexity. Intuitive dashboards allow you to dive deeper into individual jobs, datasets, and rules, helping you understand problem areas and track quality over time.

The Benefits of Improved Data Quality

By implementing effective DQM practices and leveraging tools like those provided by Actian, organizations can reap significant benefits:

1. Informed Decision-Making: High-quality data enables better insights and more accurate predictions.
2. Increased Efficiency: Streamlined data processes reduce manual data cleaning and verification time.
3. Enhanced Customer Experience: Accurate customer data leads to more personalized and effective interactions.
4. Regulatory Compliance: Well-managed data helps organizations meet increasingly stringent data regulations.
5. Cost Savings: Avoiding the pitfalls of poor data quality can save millions in potential losses and inefficiencies.

In an era where data drives business success, the importance of data quality cannot be overstated. It’s not just about having data; it’s about having data you can trust to inform critical business decisions. By implementing robust Data Quality Management practices and leveraging powerful tools like those offered by Actian, organizations can turn their data into a strategic asset, driving better business outcomes and gaining a competitive edge in their respective industries.

Remember, data quality is an ongoing process, not a one-time effort. Continuously monitoring, improving, and maintaining your data quality will ensure your organization remains agile, informed, and ready to face the challenges of an ever-evolving business landscape.

Don’t miss the opportunity to dive deeper into this topic by joining our webinar on April 1st. Click here to register!

About Traci Curran

Traci Curran serves as Director of Product Marketing at Actian focused on the Actian Data Platform. With more than 20 years of experience in technology marketing, Traci has previously held senior marketing roles at CloudBolt Software, Racemi (acquired by DXC Corporation), as well as some of the world’s most innovative startups. Traci is passionate about helping customers understand how they can accelerate innovation and gain competitive advantage by leveraging digital transformation and cloud technologies.