A data lake is an environment where a vast amount of data, of various types and structures, can be ingested, stored, assessed, and analyzed. Data lake technologies can scale to massive volumes of data, and combining datasets is easy with data stored in a relatively raw form. A data lake architecture can centralize data over distributed storage, providing a scalable, […]
Databases vs. Hadoop vs. Cloud Storage
How can an organization thrive in the 2020s, a changing and confusing time with significant Data Management demands and platform options such as data warehouses, Hadoop, and the cloud? Trying to save money by bandaging and using the same old Data Architecture ends up pushing data uphill, making it harder to use. Rethinking data usage, storage, and computation is […]
How Does Data Management Drive Efficiency for Organizations?
Data-driven analytics continue to deliver sophisticated solutions for manufacturing efficiency, early disease detection, and smart capabilities building in workplaces. Thus, industry operators and leaders continue raise their expectations and demands from data technologies with every passing year. Brent Gleeson of Forbes, who regularly contributes about organizational excellence, warns that in spite of having the best […]
Edge Computing: An Overview
Edge computing (EC) allows data generated by the Internet of Things (IoT) to be processed near its source, rather than sending the data great distances, to data centers or a cloud. More specifically, edge computing uses a network of micro-data stations to process or store the data locally, within a range of 100 square feet. […]
Data Scientist vs. Data Engineer
The Background of Data Science Roles It was thought a few years ago that 2018 would amount a huge demand-supply gap in the Data Science market as supply would fail to keep pace with the rising demand for expert data scientists. However, the buzz from Gartner, which said more than 40 percent of Data Science […]
A Brief History of Data Management
Data Management is the organization of data, the steps used to achieve efficiency, and gather business intelligence from that data. Data Management, as a concept, began in the 1960s, with ADAPSO (the Association of Data Processing Service Organizations) forwarding Data Management advice, with an emphasis on professional training and quality assurance metrics. Data management has […]
Fundamentals of Self-Service Machine Learning
The recent organizational push for self-service Business Intelligence has helped the next challenge for business users become an increasing need. How to tackle the issue of having Machine Learning (ML) models embedded in all major analytics platforms? On the one hand, embedded models offer greater freedom and control over data analysis; on the other hand, […]
Advances in Data Architecture
The continuous growth of data has led to large corporations investing heavily in technologies around large data volumes, allowing them to gain useful business intelligence that was unavailable to their smaller competitors. The evolution of public clouds has made big data technologies accessible to small businesses and startups. By using new advances in Data Architecture, […]
The Future of Data Engineering
A Data Engineering Guide reveals that while people often rely on the work of data engineers — depending on Siri for quick solutions or being enchanted by custom recommendations or promos — they often do not realize that these advanced tools can provide accurate results only because of the hard work put in by data […]
Data Architect vs. Data Engineer
Data careers are becoming increasingly important and popular all across the globe, simply because “data” is the new currency of the data economy. The pandemic gave the needed push to accelerate the digital transformation of global businesses, and currently, the primary market differentiator is an enterprise’s data infrastructure readiness. This data infrastructure comprises systems, processes, […]