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 […]
The Data Analysts of the Future: What Will They be Doing?
The need for citizen data scientists — people who can use real-time, data-powered insights — will be on the rise with the widespread availability of data and AI-enabled, self-service analytics platforms. So, the best job of the century may be at risk. Smart machine learning algorithms can analyze and interpret data, and even produce content […]
Harvest Data Lineage to Build Effective Data Governance
Being able to trace data from its origin to its destination is no longer a nice-to-have. It’s a must-have if you are to govern data — and of course you’ve got to govern data. Without metadata, data lineage can’t exist, and if data lineage can’t exist, neither can Data Governance. Metadata brings together assets and […]
Case Study: New Innovations in IoT Technologies for Manufacturers
Manufacturers want to save money, conserve energy, and reduce greenhouse gas emissions, but it’s a challenge to see where and when energy use is occurring. When the utility bill arrives, a manufacturer can see how much total energy was used, but energy use is not broken down on a machine-by-machine basis. Invisible energy use hides […]
Data Governance and Data Discovery: Enabling Data Regulation Implementation
Businesses are continuously striving to leverage data-driven insights or competitive intelligence, the concept of developing an organizational “data culture” will gain prominence. Data and data analytics will continue to play key roles in global businesses of the future. According to the article Why Data Culture Matters: “Organizational culture can accelerate the application of analytics, amplify […]
Bringing Hyperconvergence Architecture and VDIs to Everyone
A hyperconverged infrastructure (HCI) uses software and/or hardware to create an IT infrastructure that virtualizes all of the needed elements to create an efficient and highly functional computer processing system. An HCI includes compute, networking, and a storage combined together in a virtualized environment, and normally runs on easily purchased, off-the-shelf commercial servers. The primary […]
The Challenge of Scaling Transactional Databases
Generally speaking, databases are storage systems with various built-in software features to manage the movement of data within. A database management system (DBMS) describes software controlling other programs and applications. The creation and implementation of a well-designed database is a serious challenge. With the evolution of data volumes and constantly changing needs, new types of […]
Data Strategy and Serverless Computing: How Do They Work Together?
Businesses need a strong Data Strategy to manage vast amounts of data, drive innovation, develop a data culture, and to maintain a competitive advantage. Though cloud environments offer fast, high-volume data collection and scalable storage space; machine learning-powered data preparation; AI-enabled analytics; data backup and recovery facilities — leaving the developers free to pursue coding. […]
Case Study: Nearmap Advances AI-driven Location Intelligence
If a picture is worth a thousand words, but still missing valuable location data, then why not use artificial intelligence (AI) and machine learning (ML) to fill in the gaps? Take the image of Perth, Australia, below: This graphic below shows vast data sets containing buildings, green spaces, roads to travel, and parking lots. Drill […]
Data Modeling in an Agile World
Data Modeling creates a model for storing and processing data that works in a predictable, consistent manner. It includes the visual presentation of data structures, while enforcing business rules and government policies. A data model focuses on the needed data and its organization, rather than the operations performed on the data. Data Modeling is done […]