Looking back, then forward, is a traditional exercise by year-end. Which data concerns are important enough to worry about in 2024? Which of those do we stand a chance of doing something good for in 2024? Needless to say, money (budget and costs) is an issue. But even more needless to say, solving real business […]
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 […]
2023: Mitigating Data Debt by Knowing or by Guessing?
One of the newer data buzzwords is “data debt.” Actually, it is approximately 10 years old, and it became popular ever since agile people realized that postponing things creates not only technical debt, but certainly also data debt. Will we, in 2023, be better at not creating so much data debt, and will it be […]
The Hype Around Semantic Layers: How Important Are Standards?
There are several reasons why the notion of semantic layers has reached the forefront of today’s data management conversations. The analyst community is championing the data fabric tenet. The data mesh and data lake house architectures are gaining traction. Data lakes are widely deployed. Even architectural-agnostic business intelligence tooling seeks to harmonize data across sources. Each […]
Advances in Metadata Management
With the flood of data that organizations are experiencing, metadata management is no longer optional – it has become a necessity. The concept of metadata management is fairly new because older metadata services, before this rush of data, had no significant problems locating data files. Now they do. Metadata, at its most basic, can be described […]
Graph Databases: An Overview
The concept of graph databases traces back to Leonhard Euler. Euler was an 18th century Swiss mathematician who made several important discoveries in mathematics, such as infinitesimal calculus. In solving the “Seven Bridges of Königsberg” problem in 1736, Euler laid the foundations for graph theory. (He also got a fun shout-out in Hidden Figures when […]
Data Management Technology: Trends and Challenges
The last two years have been significant in the growth of Data Management technology, mainly because of the pandemic and associated factors. Almost overnight, large, medium, and small organizations located far and wide, suddenly realized the importance of online business models and hosted Data Management services. The coronavirus gave the final push to global enterprises […]
Knowledge Graph Standards in Ambient Computing
Ambient computing is a broad term that describes an environment of smart devices, data, AI decisions, and human activity that enables computer actions alongside everyday life, without the need for direct human commands or intervention. Ambient computing represents an unparalleled opportunity to enhance almost every sphere of society – from the professional to the personal. And in […]
Eradicating Broken Data Integration Approaches to Unleash Advanced Analytics
As enterprises continue to struggle with the effects of the global pandemic, the modern data analytics stack is undergoing a shock of its own. The world has changed, and we’re living in a new hybrid multicloud reality. Lower levels of the IT stack, which is to say, data centers, networks, raw storage and compute, are […]
Artificial Intelligence Augments Data Management
Artificial intelligence (AI) is now everywhere in Data Management, BI, and Data Science software, according to Mike Ferguson, Managing Director of Intelligent Business Strategies. The AI field is still young and will continue to get better as increased adoption of AI enables data and analytics software to predict, automate, and optimize, thus shortening time to […]