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Deep Learning Demystified

The “deep” in deep learning refers to the number of hidden layers involved in the design. Deep learning is a way of training artificial intelligence (AI) to recognize specific data, such as speech or faces, and to make predictions based on previous experiences. Unlike machine learning, which organizes and sends data through predefined algorithms, deep […]

So You Want to be a Data Manager?

A data manager develops and governs data-oriented systems designed to meet the needs of an organization or research team. Data Management includes accessing, validating, and storing data that is needed for research and day-to-day business operations. Currently, a wide array of organizations are using big data to gain insights into customer behavior and to provide […]

Prescriptive Analytics Use Cases

The term “prescriptive analytics” denotes the use of many different disciplines such as AI, mathematics, analytics, or simulations to advise the user whether to act, and what course of action to take. In that sense, prescriptive analytics offers an advisory function regarding the future, rather than simply “predicting” what is about to happen. This newer […]

A Brief History of Microservices

The history and origins of microservices are a continuing effort to provide better communication between different platforms, greater simplicity, and more user-friendly systems. Microservices are typically thought of as a software development technique which organizes an application as a group of loosely coupled services. It is, however, any kind of small service which interacts with […]

Demystifying Data Architecture

Ludwig Mies van der Rohe said, “Architecture starts when you carefully put two bricks together”—and Data Architecture begins upon creating, storing, and putting two or more characters together, be they sets of records, emails, pictures, audio, video. This resonated well with initial thoughts about Data Architecture, as it is comprised of things, the functionality of […]

Managing Data Governance Throughout the Data Lifecycle

Companies rely on Data Governance, the formal Data Management of people, technology, and practices, to balance data risks and opportunities. Managing Data Governance takes on even more importance across the data lifecycle, from data planning to data disposal, as shown in the diagram below Organizations tend to neglect more comprehensive Data Governance throughout the lifecycle. […]

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