Michael Carroll

The Internet Control Message Protocol (ICMP) is integral to the Internet Protocol Suite, operating primarily at the network layer. Though ICMP doesn’t manage data transfer like TCP or UDP, it plays a crucial role in network diagnostics, error handling, and control messaging.

In data-driven decision-making, Data Quality Management (DQM) ensures high standards for data accuracy, completeness, consistency, and reliability throughout its lifecycle.

Real User Monitoring (RUM) is a passive performance monitoring technique that captures, analyzes, and reports on user interactions with web applications in real-time. Unlike synthetic monitoring (which simulates user actions), RUM collects data directly from actual users, making it a vital tool for understanding...

Data acquisition (DAQ) involves gathering real-world analog signals from sensors or transducers, converting them into digital data using Analog-to-Digital Converters (ADC), and transmitting them to a computer or processing system for analysis, monitoring, or control.

Data insights are powerful revelations extracted from raw data that help businesses make more informed, strategic decisions. To drive successful decision-making, insights need to go beyond simple metrics, diving into patterns, trends, and the underlying story of the data. In this post, we’ll break down...

Anomaly detection refers to the identification of items, events, or observations that deviate significantly from the norm or expected behavior within a dataset. These anomalies are often referred to as "outliers," "exceptions," or "rare events." The goal of anomaly detection is to distinguish unusual...

Exploratory Data Analysis (EDA) is a fundamental step in data science that involves examining and summarizing the key characteristics of a dataset. It uses statistical methods and visual tools to explore data, identify patterns, detect anomalies, test hypotheses, and validate assumptions. EDA enables...

Big Data refers to datasets of enormous size, high dimensionality, and complexity, which exceed the capabilities of conventional data management and analytical methodologies.

Recent studies show that 42% of organizations are strengthening data gathering and analysis processes to meet growing requirements. They're looking at Publish/Subscribe (Pub/Sub) data streaming as a possible solution to process data more efficiently.