Whitepapers

Whitepapers Datanami's white paper database contains reports from the leading thought-leaders and idea generators in the Datanami industry.
Case Study: Learn How Mellanox used AI to maximize hardware performance

Case Study: Learn How Mellanox used AI to maximize hardware performance

Source: Concertio
Release Date: Mar 12, 2018

This paper describes an experiment in which Concertio and Mellanox teamed up for accelerating a specific networking use-case running on Mellanox’s ConnectX-3 Pro Ethernet cards. The results showed that the settings discovered automatically by the AI-powered Optimizer Studio tool outperformed the best settings found through manual tuning, and were discovered faster. Read more…

Drive Next-Generation Customer Experiences with Real-Time Connected Product and Service Analytics

Drive Next-Generation Customer Experiences with Real-Time Connected Product and Service Analytics

Source: SAS, Intel and Hortonworks
Release Date: Feb 8, 2018

During the last 25 years, manufacturers have dramatically advanced capabilities in product design and manufacturing quality. Today, the industry has turned its focus to improving customer experiences, but organizations will need to gain new skills in order to capture this value. Read more…

More than Algorithms and Accelerators: ROI for Machine Learning Requires Collaboration and Trusted Partners

More than Algorithms and Accelerators: ROI for Machine Learning Requires Collaboration and Trusted Partners

Source: Cray
Release Date: Feb 1, 2018

Some of the biggest challenges in useful machine learning, deep learning and artificial intelligence projects stem from the fact that learning systems exist in the middle of a wider workflow. Read more…

Drive Next Generation Performance with Real-Time Connected Manufacturing

Source: SAS, Intel and Hortonworks
Release Date: Jan 18, 2018

Digital transformation is now essential for corporate survival. The most significant digitization strategy over the past three years is the Internet of Things. but how does the IoT promise to drive such value? Read more…

More than Algorithms and Accelerators: ROI for Machine Learning Requires Collaboration and Trusted Partners

Source: Cray
Release Date: Jan 17, 2018

Some of the biggest challenges in useful machine learning, deep learning and artificial intelligence projects stem from the fact that learning systems exist in the middle of a wider workflow. Read more…

Anzo Smart Data Lake for Enterprise Data on Demand

Source:
Release Date: Nov 7, 2017

Only with a rich and interactive semantic layer can the data and analytics stack to deliver true on-demand access to data, answers and insights – weaving data together from across the enterprise into an information fabric. Read more…

Striim

The Real Costs and Benefits of Open Source Data Platforms

Source: Striim
Release Date: Oct 19, 2017

Many enterprises have embraced “open source first” strategies with the requirement that there be robust commercial support behind it. But how far can enterprises take this strategy? The strongest proponents and pioneers of open source software including Google, Facebook, and Netflix continue to also use vendor-specific technology solutions that deliver unique value. Read more…

How to Solve the Unstructured Data Paradox

Source: WekaIO
Release Date: Oct 13, 2017

Organizations with performance sensitive or large stores of unstructured data have a new option to consider. In most cases these organizations have a compute cluster already established for processing. WekaIO’s proposition is to simplify data storage by making it a scalable application that leverages the compute cluster to provide storage services. Read more…

Workload-Aware Auto-Scaling; A New Paradigm for Big Data Workloads

Source: Qubole
Release Date: Oct 12, 2017

This technical white paper explains the differences between what cloud provider auto-scaling was designed to support vs. what is required to scale cloud resources with Hadoop, Spark and big data workloads. Read more…

How to Drive Big Data Projects to Maturity

How to Drive Big Data Projects to Maturity

Source: Qubole
Release Date: Jun 29, 2017