Getting Started With Data Analytics Acceleration Library

Getting Started With Data Analytics Acceleration LibraryShare your comment!

As the size of data grows, so does the difficulty performing analysis. The larger the data, the more difficult in terms of time and resources that analysis requires. For instance, most web servers log all page requests, including asset files such as CSS, image and JavaScript. And there are a lot of them—the days of opening a server log file with Notepad to examine it are over. You need a big data approach. And that is what Intel has provided with its Data Analytics Acceleration Library (DAAL).

DAAL to the Rescue

Analytics is a technical problem that solves a business one. The technical part of the problem is how to perform analytics on large data. The business part is using analytics to make good business decisions. The final objective of DAAL is to provide the information necessary to make good business decisions.

A large part of data analytics is machine learning. This technology is not new, but Intel has provided a comprehensive package with which developers can easily add machine learning to their arsenal. DAAL provides all of the building blocks for machine learning, and these blocks can then be used to perform analytics for decision making.

Large data analytics invariably introduce bottlenecks. This is understandable when you consider the large amounts of data that are transported over a communication layer. DAAL manages these bottlenecks during the entire process. You’re free to manage your analytic flow and focus on solving the business problems.