Within the last several years, the marketplace has shifted from industrial-produced to data-based. Consequently, many companies have a strong drive to become data-driven, from financial firms to nonprofits. Yet, when C-suite managers and others discuss making money from data, they see the face of data analytics and Data Science. These conversations miss the Data Architecture and Data Management fundamentals […]
What Is Data Modeling? Types, Benefits, Uses
Data Modeling describes the plans and activities around diagramming data requirements for business operations across one or more systems. This blueprint defines unique data entities (such as tables, systems, concepts, and hubs) and their characteristics (such as inheritance, importance, and physical structures) along with how the data flows between entities. Organizations create or update data models anytime, depending […]
Is Your Data Ready for Generative AI?
Generative AI (GenAI) is all the rage in the world today, thanks to the advent of tools like ChatGPT and DALL-E. To their credit, these innovations are extraordinary. They’ve put the power of artificial intelligence and machine learning (AI/ML) into the hands of everyday users. However, these tools have also skewed our perceptions of what […]
Managing Data as a Product: What, Why, How
The concept of managing “data as a product” involves a paradigm shift. By treating data as a product designed for consumer use, rather than a pool of semi-chaotic information, businesses can increase their profits. Many businesses have set up customized data pipelines – or other extreme and expensive steps – in unsuccessful efforts to maximize the […]
Core Data Concepts for Digital Transformation
Without a clear understanding of core data concepts, communications around implementing an organizational Data Management initiative can become a muddle. As different teams come together to plan and organize data activities, they must integrate what they mean about data with any technologies. For example, take the term “Data Governance.” Data engineers building systems and tools to enable […]
Usability and Connecting Threads: How Data Fabric Makes Sense Out of Disparate Data
Generating actionable insights across growing data volumes and disconnected data silos is becoming increasingly challenging for organizations. Working across data islands leads to siloed thinking and the inability to implement critical business initiatives such as Customer, Product, or Asset 360. As data is generated, stored, and used across data centers, edge, and cloud providers, managing a […]
Distributed Tracing in Microservices: A Comprehensive Guide
Today, one of the most popular techniques to achieve high levels of performance and reliability in your software applications is by leveraging the power of microservices architecture. This architectural style breaks down a monolithic application into smaller, more manageable services that can be independently developed, deployed, and scaled. While this approach offers numerous benefits, it […]
Distributed Data Architecture Patterns Explained
Distributed data architecture, models using multiple platforms, and processes for data-driven goals continue to generate increased interest. As William McKnight, president of McKnight Consulting Group (MCG) and well-known data architecture advisor, says, “Seldom a database vendor does not interact with concepts around distributed data architectures: the data lakehouse, data mesh, data fabric, and data cloud, and I am […]
Data Security Posture Management (DSPM): A Technical Explainer
Data is growing on a massive scale – it spreads across geographies, systems, networks, SaaS applications, and multi-cloud. Similarly, data security breaches are following suit and increasing in number (and sophistication) every year. Organizations must modernize their approach to cybersecurity and start giving equal attention to data and infrastructure. Here, data security posture management (DSPM) comes into the […]
Data Mesh: A Pit Stop on the Road to a Data-Centric Culture
The noble effort to build a “data-centric” culture is really a journey, not a destination. With that perspective, we can understand that no matter how good a given environment seems to be –especially compared to whatever existed before – there’s always room for enhancement. As more technologies, strategies, and disciplines emerge, the ongoing evolution ensures constant improvement. […]