Como você referencia os padrões de qualidade de dados em seu trabalho?

Data quality is the cornerstone of trust in the products, analysis and reports being created with data and decisions being made based on them. Referencing data quality standards in daily work, basic contribution to ensuring trust in data as fundament.

data quality standards are extremely important to guarantee that data is accurate, reliable and accessible. It improves the credibility of your data analysis, advances interoperability across multiple systems, reduces the risks associated with data errors and inconsistencies and enhances the trust of stakeholders.

Bei der Integration von Datenqualitätsstandards in unsere Projekte ziehen wir branchenspezifische Richtlinien heran. Im Gesundheitswesen orientierten wir uns am HIPAA-Standard, was das Vertrauen unserer Kunden in unsere Datenmanagement-Praktiken stärkte, indem wir gleichzeitig Datenqualität und Compliance sicherstellten.

Leveraging established data quality standards is a smart approach. It allows you to benefit from the collective knowledge and best practices that have already been developed, saving time and resources. These standards provide a solid foundation for your data audit and review process. They can help ensure consistency, reliability, and accuracy in your data, which are crucial for informed decision-making. These standards provide a great starting point, it’s important to adapt them to your organization’s specific needs and context.

Políticas e padrões são necessários para o bom funcionamento de qualquer função de dados, inclusive a qualidade de dados. Esses documentos devem ser baseados em referências técnicas consagradas. No caso da Qualidade de Dados, costumo a utilizar como referência o DAMA-DMBoK e a ISO 8000. São ótimas referências, mas suas implantações devem ser adaptada as características da empresa. Geralmente gosto de trabalhar com a definição de uma politica de qualidade de dados - que define as principais diretrizes, um procedimento técnico que possui um nível de detalhe maior e o desenho dos processos de qualidade de dados e os seus respectivos indicadores. Como isso temos o que deve ser feito, como ser feito e como medir e avaliar o resultado na empresa.

obtaining accurate data quality standards involves exploring reliable sources within your industry. You should start by consulting industry specific regulatory bodies, as they frequently publish data management and quality guidelines. ISO (International Organization for Standardization) and ANSI (American National Standards Institute) also provide widely recognized standards. Furthermore, academic journals and industry publications can provide insights into current best practices and emerging standards.

I've found it helpful to also reference the Data Management Association (DAMA), ISO 9001 for more information on data quality. Consider joining forums, networking with industry professionals and events focused on data to improve your understanding in this area.

Unsere Arbeit basiert auf einer Kombination aus internationalen Standards wie ISO 8000 und branchenspezifischen Normen, um Datenqualität und Interoperabilität über Plattformen zu gewährleisten. Bei einem multinationalen Unternehmen implementierten wir ISO 8000 für effektive Datenkatalogisierung.

Reference data quality standards in your work by clearly documenting the standards you adhere to and how they apply to each project. Incorporate standards into project plans, data quality assessments, and reporting. Ensure all team members are aware of these standards and understand their application to ensure consistent adherence.

Die klare Dokumentation und Kommunikation von Datenqualitätsstandards gegenüber Stakeholdern ist essenziell. Wir erstellen Richtlinien und Schulungen, die das Verständnis für die Bedeutung und Anwendung dieser Standards vertiefen, was das Bewusstsein und die Einhaltung von Datenqualität fördert.

Various data quality management tools and software can help you reference and adhere to data quality standards. These tools often include features for data profiling, cleansing, validation, and monitoring aligned with industry standards. Look for tools that offer customization options to incorporate specific standards relevant to your projects.

Um die Einhaltung von Datenqualitätsstandards zu automatisieren, nutzen wir zetVisions SPoT. Dieses Tool ermöglichte es uns, in einem Projekt für ein Finanzinstitut, die Datenvalidierung effizient zu gestalten und Compliance sicherzustellen.

Die sich ständig ändernden Datenqualitätsstandards erfordern eine agile Anpassung unserer Datenmanagement-Strategien. Für einen Retail-Kunden entwickelten wir ein Framework, das schnelles Reagieren auf neue oder sich ändernde Standards ermöglicht und unsere Datenprozesse entsprechend anpasst.

Challenges may include the complexity of standards, keeping up with updates, and applying standards across diverse data sources and systems. Additionally, achieving buy-in from all stakeholders for the adoption of these standards can be difficult, especially if the benefits are not immediately evident.

Beyond the direct application of data quality standards, consider the broader implications for data governance and compliance within your organization. Educate stakeholders on the importance of these standards for regulatory compliance, operational efficiency, and competitive advantage. Regularly review and update your approach to incorporating standards, considering evolving business needs and technological advancements. Building a culture that values data quality and standardization is key to long-term success.