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Data Mesh Architecture Fundamentals

A data mesh architecture is a network design that allows data to be routed across multiple paths between network nodes. Whereas traditional network designs routed data along a single path, data mesh architecture enables data to be routed simultaneously across multiple paths between nodes.  This architecture provides several advantages over other architectures, such as a hub-and-spoke […]

Primary Data Modeling Techniques

Data Modeling techniques are used to create a map or blueprint showing how an organization gathers and processes data. Data models help to define the logical structure for an organization’s data. Data Modeling techniques are necessary for businesses wanting to maximize and streamline their ability to analyze and understand data. While developing the model, the […]

Types of Analytics Used in Organizations

Data analytics in businesses help uncover competitive intelligence, actionable insights and trends. Different types of analytics enable businesses to gain an edge over their competitors. In the “data first” era, data-driven insights and decisions have become the key drivers of business performance. This post reviews the different types of data analytics routinely used in enterprises. […]

Five Essential Data Architecture Principles

Data Architecture principles are a set of policies that govern the enterprise data framework with its operating rules for collecting, integrating, using, and managing data assets. The basic purpose of the Data Architecture principles is to keep the supportive data framework clean, consistent, and auditable. The overall enterprise Data Strategy is built around these principles. […]

Trends in Data Architecture

What role have Data Management and Data Architecture played in data-driven organizations, especially during the tumultuous and uncertain period at the beginning of the COVID-19 pandemic? Industry thought leader Donna Burbank, the Managing Director of Global Data Strategy, discussed these issues in her presentation Trends in Data Architecture at DATAVERSITY®’s Data Architecture Online conference last July.  Burbank shared insights from a 2020 […]

Data Quality Management 101

Data Quality Management is necessary for dealing with the real challenge of low-quality data. Data Quality Management can stop the waste of time and energy required to deal with inaccurate data by manually reprocessing it. Low-quality data can hide problems in operations and make regulatory compliance a challenge. Good Data Quality Management is essential for […]

Challenges of Data Governance in a Multi-Cloud World

Today, it would be really hard to find a business totally free of cloud services. In spite of battling centralized “no-cloud” policies in some enterprises, individual departments, work groups, and units are increasingly subscribing to services for data storage and backup, media services, CRM, hosted analytics, and more. Even developers are using Infrastructure-as-a-Service (IaaS) and […]