Twenty years ago, a startup called VMware brought in business by providing a platform to create nonphysical machine virtualizations, such as Linux, Windows, and others. As server processing capacity increased, basic applications couldn’t maximize the use of all the abundant new resources. Enter Virtual Machines (VMs), designed to run software on top of a physical […]
Artificial Intelligence, Machine Learning, and Data Protection
Artificial intelligence and machine learning techniques are altering the way organizations gather, process, and protect data. They are being used to gather massive amounts of information about internet users in the form of big data, and to secure and protect it. The challenge is how to maximize the use of big data, while simultaneously safeguarding […]
Seven Principles to Put DataOps into Practice
You’re going to hear a lot more about DataOps in the coming months and the next couple of years. That’s the word from DataKitchen co-founder Eric Estabrooks. You know something is gaining market traction when Gartner includes it in a hype cycle report. The research firm did just that for DataOps in its Hype […]
Case Study: Centrica Succeeds with Data Discovery at Scale
“When you’ve got a mass of data, how do you analyze that data and get to a point where you can get the gemstones, the diamonds out of it?” Mike Young, Chief Information Officer with Centrica, knows what it’s like to wade through a sea of petabytes and terabytes to find value. Centrica is an […]
Implementing Data Strategy Across the Data Lifecycle
Organizations wishing to implement a Data Strategy—a set of decisions that form a pattern, charting a high-level course of action—face significant challenges in unifying their message across the data lifecycle. Only 30% of companies have a clear organizational Data Strategy, leaving their different departments to figure out how to manage company data assets. Moreover, two […]
Data Management vs. Data Strategy: A Framework for Business Success
In a DATAVERSITY® interview, Donna Burbank, the Managing Director at Global Data Strategy, said: “The difference between Data Management vs. Data Strategy is almost in the definition of the two words. Think about your money. If you’re just managing it, you’re sort of just getting by, but if you’re thinking strategically, you’re really thinking of […]
A Brief History of Data Silos
The original purpose of a data silo was to keep secrets. People have been keeping secrets for a long, long time. Prior to the written word, keeping a secret meant not sharing specific information with anyone else, verbally. And then came the written word. Secrets could be shared accidentally, or even stolen. Life became more […]
The Data Warehouse, the Data Lake, and the Future of Analytics
Data lakes were created in response to the need for Big Data analytics that has been largely unmet by data warehousing. The pendulum swing toward data lake technology provides some remarkable new capabilities, but can be problematic if the swing goes too far in the other direction. Far from being at the end of this […]
NoSQL Databases: The Versatile Solution for Continuous Intelligence
Most businesses tend to rely on relational database management systems (RDBMS) to provide business insight, including continuous intelligence. Cloud relational databases have improved computing power they bring to the table, to handle more massive amounts of data. However, relational databases, even ones in the cloud, face two issues. They have a harder time with the […]
Working with Metadata Management Frameworks
Metadata Management will grow into 2021 and beyond. According to a DATAVERSITY® Trends in Data Management Report, 84 percent of business respondents had a Metadata Management initiative in place or had plans for one. MarketWatch, a consulting firm, expects massive growth by 2026. How much success a company will have with Metadata Management will depend […]