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Azure Data Lake

What is High Performance Data Analytics? And How it Works?

High performance data analytics (HPDA) is a method of analyzing large data sets that utilizes high performance computing (HPC). HPDA combines advanced computing techniques with analytical algorithms to identify patterns and insights that would be difficult or impossible to discern using traditional methods. By leveraging the power of HPC, HPDA can process vast amounts of data quickly and efficiently, enabling businesses to make informed decisions and gain a competitive advantage.

In what way does High Performance Data Analytics help us?

High-performance computing (HPC) has played an important role in big data analytics for many years. The massive amount of data generated today will require new forms of high-performance computing to unlock it. Big data analytics and high-performance computing are converging to form High-Performance Data Analytics.

The goal of high-performance data analytics is to find insights from extremely large data sets within a short period of time. Powerful analytical software is run using the parallel processing of high-performance computing.

The demand for high-performance data analytics infrastructure is growing rapidly among government and private companies that need to combine high-performance computing with data-intensive analyses.

How does High Performance Data Analytics benefit companies?

High-performance computing, which is essential for complex modeling and simulation, is not available to big data analytics methods such as Hadoop and Spark. Through high-performance data analytics, once incompatible systems are brought together. This convergence leads to better decisions due to an acceleration of insights.

Furthermore, high-performance data analytics provides super fast communication between processing elements to avoid input/output bottlenecks. As well to error detection, graph modeling, graph visualization, streaming analytics, exploratory data analysis, and architecture analysis, high-performance data analytics offers other benefits.

Framework for High Performance Data Analytics

A high-performance data analytics framework provides a means to improve productivity and performance for data analysts.

Using high-performance computing systems to leverage framework-as-an-application is called framework-as-an-application.

The following techniques can be used to analyze data on high-performance computing systems:

  • Modeling and visualization of graphs is used in graph analytics to understand large, complex networks.
  • Analyzing computationally intensive problems using innovative techniques.
  • Analyzes streaming data in real-time with new algorithms for high-bandwidth and high-throughput.
  • Analyzes massive streaming data sources in exploratory data analysis.
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