In the last few decades, neural networks have evolved from an academic curiosity into a vast “deep learning” industry. Deep learning uses neural networks, a data structure design loosely inspired by the layout of biological neurons. These neural networks are constructed in layers, and the inputs from one layer are connected to the outputs of […]
Data Fabric vs. Data Mesh
In the hyper-connected world of the cloud and the Internet of Things (IoT), every computing network device is connected to another through a complex, interconnected network. This poses a serious challenge to future Data Management, as the ultimate goal of Data Management is the sharing of business data across disparate platforms and technologies. This article […]
Big Data Ecosystem Updates: Hadoop, Containers, and VMs Explained
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 […]
Knowledge Graphs for Robust Data Governance
More data, more sources, more conflicts. More self-service reporting, more cross-functional analytics, more government and industry regulations. Without a way to govern all the data in their possession, businesses are not going to do well at creating reports or dashboards or building data consensus across departments. Nor will they feel confident that they’re not missing […]
A Brief History of Database Management
A database management system (DBMS) allows a person to organize, store, and retrieve data from a computer. It is a way of communicating with a computer’s “stored memory.” In the very early years of computers, “punch cards” were used for input, output, and data storage. Punch cards offered a fast way to enter data and […]
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 […]
Is Streaming Analytics the Future of Business Analytics?
Analyzing data as it is created or changes? Is that possible? Now it is, with streaming analytics, which monitors and responds to continuously flowing data from connected devices and live data channels like the sensors, machine logs, relational databases, social media feeds, location data sources, and so on. The core differentiator of streaming analytics is […]
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 […]
A Brief History of Data Science
The term “Data Science” was created in the early 1960s to describe a new profession that would support the understanding and interpretation of the large amounts of data which was being amassed at the time. (At the time, there was no way of predicting the truly massive amounts of data over the next fifty years.) […]
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 […]