A data mesh challenges the traditional centralized Data Architecture by advocating a distributed and domain-oriented architecture. Data mesh promotes the idea of treating “data as a product,” where each domain or business unit becomes responsible for its own data products. By doing so, individual domains gain autonomy over their data needs and can make faster […]
Hybrid Architectures in Data Vault 2.0
Are you drowning in data? Feeling shackled by rigid data warehouses that can’t keep pace with your ever-evolving business needs? You’re not alone. Traditional data storage strategies are crumbling under the weight of diverse data sources, leaving you with limited analytics and frustrated decisions. But what if there was a better way? A way to […]
Ask a Data Ethicist: Can We Trust Unexplainable AI?
In last month’s column, I asked readers to send in their “big questions” when it comes to data and AI. This month’s question more than answered that call! It encompasses the enormous areas of trust in AI tools and explainability. How can we know if an AI tool is delivering an ethical result if we have […]
Data Privacy vs. Data Security
Data privacy refers to a framework of laws, protocols, and controls designed to protect personal data from unauthorized access and use. It encompasses a range of information, including but not limited to names, addresses, financial details, social security numbers, and online activities. Data security refers to the controls, protocols, and industry standards designed to protect digital […]
Creating a Data Quality Framework
An organization can define its Data Quality goals and standards, and the steps needed to accomplish those goals, by creating a Data Quality framework. Creating it includes an assessment of the organization’s current Data Quality. A Data Quality framework can be described as an instruction manual for improving the quality of the data. With a […]
The Cool Kids Corner: CLEAR Communication
Hello! I’m Mark Horseman, and welcome to The Cool Kids Corner. This is my monthly check-in to share with you the people and ideas I encounter as the data evangelist with DATAVERSITY. (Read last month’s column here.) This month, we’re talking about communication. Communication is the cornerstone of socializing anything you do with data, whether that’s […]
Dynatrace Adds Data Observability to Analytics and Automation Platform
According to a new press release, Dynatrace has introduced AI-powered data observability capabilities for its analytics and automation platform. Named Dynatrace Data Observability, the feature aims to enhance the reliability and accuracy of data in the Dynatrace platform for business analytics, cloud orchestration, and automation. The technology allows teams to rely on high-quality data, ensuring […]
Data Governance Trends in 2024
Companies are more determined than ever in 2024 to improve their Data Governance (DG) programs, the bedrock that supports harmonized data activities across organizations…
Building Trust in the Digital Age: The Role of Data Verification
Data has famously been referred to as the “new oil,” powering the fifth industrial revolution. As our reliance on data-intensive sectors like finance, healthcare, and the Internet of Things (IoT) grows, the question of trust becomes paramount. Trust is a multifaceted issue when dealing with data and events, and one core component is data verification. […]
data.world Integrates with Snowflake to Provide New Data Quality Metrics
According to a new press release, data.world has announced an integration with Snowflake, a data cloud company, to provide new data quality metrics and measurement capabilities to enterprises. As one of the first data catalogs to support Snowflake’s data quality metrics, data.world’s Snowflake Collector allows enterprise data teams to measure data quality across their organization […]