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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 […]

The Fundamentals of Deep Reinforcement Learning

Reinforcement Learning (RL), a “niche” Machine Learning technique, has surfaced in the last five years. In context-based decision making, Reinforcement Learning helps the machine take action-provoking decision making through a trial-and-error approach to achieve the optimal algorithmic model for a situation. Furthermore, the machine is trained through a reward/penalty-based feedback mechanism, the goal of which […]

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 […]

Graph Databases vs. Key-Value Databases

Graph databases and key-value databases have very different features and are used for accomplishing different tasks. Key-value databases are streamlined and fast, but are limited and not as flexible. Graph databases, on the other hand, are very flexible and great for research, but not terribly fast. Both typically use a non-relational foundation. The two key […]

Scaling the Analytics Team: Developing Key Roles

In an enterprise analytics team, different roles exist to fill different needs, and those needs must be met in order to be successful. Launching an analytics program doesn’t necessarily require a massive influx of personnel before producing usable insights from data, yet it’s important that critical roles are filled, whatever the size of the team. […]

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