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Data is critical to every aspect of running a modern business. Today, data is available in several types of media, such as text, images, logs, graphs, and more. Not only does data come in different forms, but it also comes in from various sources, such as social media, edge devices, IoT, sensors, and others. It is increasingly clear that rapid growth in volume, velocity, and variety of available data is straining traditional strategies for data management and analysis.
Data analytics is the process of analyzing raw, structured, and unstructured data to identify trends and answer questions. This type of analysis allows business to interpret and communicate meaningful data patterns. Various approaches to data analytics include:
Organizations can apply analytics to business data to describe, predict, and improve business processes and outcomes.
Organizations rely on data analytics to make better business decisions. Having the right infrastructure in place to run such workloads not only speeds up the analytics process, but it also provides a robust architecture to prevent any unplanned outages. Data analytics infrastructure needs to be powerful, highly available (HA), and flexible, as does any infrastructure designed for business-critical applications.