Overview
What is data quality?
The quality of your data determines its utility. If your data isn’t useful and can’t provide insights, then it’s not quality data. Ideal data can be easily processed and analyzed, and is relevant to your users. Focus on accuracy, completeness, consistency, timeliness, and accessibility. If this doesn’t sound like your data, it’s time for a new approach.
Driving outcomes with data quality
With quality data, your business can gain insights that will help streamline processes, improve services, and boost growth and revenue. The better your data, the better your insights will be — and the better your business will be now and in the future. And if you have quality data, you likely have good data management practices, which make for better security, organization, and efficiency.
Five critical practices to improve data quality
1. Eliminate silos
Siloed data will never deliver it’s true value. With silos, it’s impossible to get a complete view of your business and to have a single source of truth. With data isolated, users in different departments duplicate their data instead of sharing it, which creates confusion, inconsistencies, and lost agility. By eliminating silos, everyone in your organization can see all your data all at once and have a single source of truth.
2. Make data accessible to all your users
Though data has traditionally been owned by specific business units that collect and use it for their own purposes, this approach produces narrow-minded results that don’t benefit the business as a whole. Data should to be made accessible to all types of users across the organization. The true value of data can only be realized when 100% of your data is available to 100% of your users.
To truly achieve data-driven success, businesses need to encourage collaboration between business units and shift to an enterprise-focused approach. When everyone in every department can ask cross-functional questions and work off a single source of truth, there can be more insights and innovation.
3. Use the right data
Data quality is about more than accessibility — it’s about relevancy. The best data combines multiple sources to create a broad and complete view of the organization, so you can answer the most complex questions. By tapping into diverse and creative data sources, you can gain a competitive advantage that will help your business grow and find success.
4. Secure your data
Safeguarding your data is critical to ensuring customer trust and business security. And with the amount of data flowing into modern organizations, keeping it all accessible for necessary users yet protected is a key differentiator for successful businesses. To keep your data secure while allowing access within the organization, develop a data analytics ecosystem that focuses on managing vulnerabilities, encryption, and authentication, as well as role-based access and fine-grain security controls.
5. Treat data quality as a process
Creating value from data is more than just delivering “one off” insights. While an established data management system helps, businesses need to cleanse and maintain their data, and build rigor around these practices.True success requires operationalizing your data, and continually reevaluating how your data can work for you and what data and data analytics processes serve your business.Everything from data storage to analysis to application needs to be streamlined, managed, and automated.
Becoming future-ready
Inadequate data — whether it’s the wrong data for the job, or just inaccessible or inaccurate — will compromise the entirety of your data and prevent you from making informed business decisions. Data quality lays the groundwork for all data-driven outcomes, and the quality of your data will determine the caliber of the insights you’re able to derive.
To truly become future-ready, create an effective and widely adopted data culture with a modern data analytics platform that can accommodate unlimited users and concurrency, continually optimize, and help create insights and drive outcomes.