Katana Graph’s Analytics Python Library

By: Katana Graph

July 21, 2022

Katana Graph’s Analytics Python Library

As businesses grow and face increasing data challenges, they must find ways to tackle more expansive problems in shorter time windows. The most essential tools a company has at its disposal for addressing real-world data problems are modern algorithms. Businesses that take an algorithmic approach can tackle bigger problems with larger numbers of variables and can make better decisions than those that don't. Data is unquestionably the world’s most valuable resource today.

Over the past few weeks, we've led you through an overview of our set of currently available algorithms for analyzing graphs and our rationales as to why they are relevant and necessary. Katana Graph's Python Library of Graph Analytics is a collection of algorithms to help you solve increasingly complex problems and get answers in time for them to be useful. Graphs are essential in many areas today, including social networks, telecommunication networks, financial networks, web traffic analysis, biochemical pathways, and more. To take the best advantage of this emerging application area, data scientists working with linked data sets such as social networks need a graph data suite of tools like our analytics library.

Graphs in practical applications tend to range from large to incomprehensibly immense. For example, graphs involving the evaluation of influence in social networks can involve 100 billion edges, so high-performance parallel computing has become increasingly important.

The Katana Graph Python Library of Graph Analytics provides a collection of algorithms to solve problems in the area of graph analytics. Katana Graph and Intel created the Python library to give users an easy way to implement graph analytics algorithms on their own data sets.

Our product has at its core the Katana Graph Engine with its accompanying partitioner, communication, virtualization, and storage technology modules. This software, along with the culmination of more than a decade of advanced research in graph technology and high-performance computing, will expand the role of graph computing across the technology industry.

If you missed any part of this Katana Graph's Python Library series, we recommend learning more about our graph analytics library. The library contains thirteen algorithms, including:

Our Python Library of Graph Analytics gives enterprise users a good balance of speed and scalability, which is essential for the demands of large data sizes and shared computation. It provides solutions to help your business make timely decisions. Interested in what we can do for your business? Contact us today to schedule a time to talk!

Katana Graph and Your Business Analytics Needs

Katan Graph can bring your data into brilliant focus faster than was previously dreamed possible, and without workflow disruption, overspending or massive restructuring of your data. We thrive on testing new ideas and solving problems thought to be intractable. A philosophy of continuous improvement is the core of our success.

The Katana Graph Intelligence Platform scales beyond 256 machines and runs ten to one hundred times faster than competing graph platforms. Our engine runs on cloud computing platforms including Microsoft Azure, Google GCP, and Amazon AWS.

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