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Making Machine Learning Simple

For enterprises who need to jump start into machine learning, Databricks provides the performance, reliability, and ease of use to tackle machine learning with big data. With Databricks, teams will be able to focus on solving hard machine learning problems instead of supporting infrastructure. To learn more on making machine learning simple download this white paper.

Solving Advanced IoT Analytics with the Databricks Just-in-time Approach

ESG’s recent 2016 IT Spending Intentions Survey reveals that both organizations in the throes of IoT, as well as those with plans to go down that path, anticipate that IoT will create business value across several categories including operational efficiencies, better customer service, new products and services, and new business models. Learn the keys to unlocking the potential from IOT Analytics.

Configuration for Big-Data-as-a-Service

This white paper describes a new solution for Big-Data-as-a-Service combining the BlueData EPIC (Elastic Private Instant Clusters) software platform with the HPE Elastic Platform for Big Data Analytics (EPA). BlueData is transforming how enterprises deploy their Big Data applications and infrastructure. To learn more about Big-Data-as-a-Service download this white paper.

Bare-Metal Performance for Big Data Workloads on Docker Containers

In a benchmark study, Intel compared the performance of Big Data workloads running on a bare-metal deployment versus running in Docker containers with the BlueData EPIC software platform. The study found that it is possible to run Big Data workloads in a container-based environment without sacrificing performance. The benefits include agility, flexibility, and cost efficiency. Data science teams can get on-demand Hadoop and Spark clusters, while leveraging enterprise-grade security in a multi-tenant architecture. Get the white paper to learn about this breakthrough benchmark study.

insideHPC Special Report Riding the Wave of Machine Learning & Deep Learning

AI, machine learning and deep learning are transforming the entire world of technology, but these technologies are only making headway now due to the proliferation of data. Companies first steps should include the “Five-step enterprise AI strategy”. To learn more about riding the wave of machine learning and deep learning download this insideHPC special report.

How to Achieve a Customer Centric Culture Supported by Data Driven Insights

A company’s culture informs its every effort, from marketing and outreach to the ways in which internal departments work together. In today’s competitive business environment, it’s imperative to implement a customer-centric culture that permeates the entire business, from the very top of the organization down throughout every department sector. To learn more about how to achieve a customer-centric culture supported by data-driven insights download this white paper.

Data Capture and Science Strategy

Innovative drug development organizations are leveraging scientific and technical advances to data capture data that is increasingly multidimensional and information rich. However, existing data capture and sharing processes are often unable to support efficient integration and interpretation of this data. To learn more about available technologies available for data capture and relation science strategy download this white paper.

2017 State of Analytics Adoption Report

The annual State of Analytics Adoption Report by Logi Analytics provides insights for executives, product managers, and technology leaders on how broadly and deeply users are adopting business intelligence and analytics tools. Survey respondents included members of IT teams who provide analytics tools to end users, as well as the end users of BI and […]

Advanced Analytics, The Modern Marketer’s Best Friend

Download our free white paper to get a global understanding of how analytics are shaking up marketing and what you can do about that!

Architecting for Access: Simplifying Analytics on Big Data Infrastructure

Whether you’re upgrading your current solution or rolling out a brand new platform, planning and executing an analytics workload today requires answering many tough questions.
This eBook from O’Reilly shares:
• How to choose between a data lake or analysis on the fly
• Tips on finding front-end tools that delight users
• Evaluations of hundreds of permutations of technology stacks
• Advice on how to make data your endgame, not opinion