Understanding data health involves monitoring and analyzing diverse aspects of data systems – referred to as data observability – to ensure optimal performance and reliability. Metrics are crucial, providing quantitative insights into data flow, processing times, and system resource utilization. They also help identify patterns and detect anomalies in real time. Logs offer a historical record of […]
Data Architecture Trends in 2025
A modern data architecture is required to support the data-driven organization that every enterprise wants to be. Without a solid data architecture – composed of the models, policies, rules, and standards you set for how data is collected, stored, managed, and used – your ability to attain a holistic view of your business, make informed […]
2025’s Game-Changers: The Future of Data Engineering Unveiled
As the digital world grows increasingly data-centric, businesses are compelled to innovate continuously to keep up with the vast amounts of information flowing through their systems. To remain competitive, organizations must embrace cutting-edge technologies and trends that optimize how data is engineered, processed, and utilized. From decentralized frameworks to AI-driven advancements, 2025 is poised to […]
Achieving Cost-Efficient Observability in Cloud-Native Environments
Cloud-native environments have become the cornerstone of modern technology innovation. From nimble startups to tech giants, companies are adopting cloud-native architectures, drawn by the promise of scalability, flexibility, and rapid deployment. However, this power comes with increased complexity – and a pressing need for observability. The Observability Imperative Operating a cloud-native system without proper observability […]
The Benefits of Observability Go Beyond Network Monitoring
As networks and systems grow ever more complex, observability is becoming increasingly essential. Cloud computing has moved network operations outside the traditional data center, and the addition of mobile networks, edge computing, and hybrid work has added to the breadth and complexity of today’s enterprises. Observability has proved to be highly effective in measuring the […]
How AI Will Fuel the Future of Observability
We’re seeing a lot of convergence in the market between observability vendors and companies positioned as artificial intelligence (AI) companies. It’s a natural marriage, since AI has the potential to significantly improve what observability does. The question is how to make the best use of AI to support observability in discovering an organization’s unknowns, providing […]
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 […]
Understanding the Impact of Bad Data
Do you know the costs of poor data quality? Below, I explore the significance of data observability, how it can mitigate the risks of bad data, and ways to measure its ROI. By understanding the impact of bad data and implementing effective strategies, organizations can maximize the benefits of their data quality initiatives. Data has become […]
The Rise of RAG-Based LLMs in 2024
As we step into 2024, one trend stands out prominently on the horizon: the rise of retrieval-augmented generation (RAG) models in the realm of large language models (LLMs). In the wake of challenges posed by hallucinations and training limitations, RAG-based LLMs are emerging as a promising solution that could reshape how enterprises handle data. The surge […]
Data Observability Use Cases
“Data observability” can be described as the practice of monitoring the “health and state” of data pipelines in your system. This practice encompasses some technologies and activities that enable business operators to identify, examine, and solve data-related problems in near real time. Though organizations rely heavily on accurate and reliable data to make informed decisions, […]