Addressing the Systemic Shortcomings of Cloud Analytics

Logo
Presented by

Kaige Liu, Sr. Solutions Architect

About this talk

Learn how to increase the value of your analytics investment with existing open source technologies like Apache Kylin, Spark, and Mondrian. Talk #1: Addressing the Systemic Shortcomings of Cloud Analytics As we enter what some have called The Golden Age of Analytics, there are still some fundamental challenges that plague even the largest and most sophisticated cloud analytics adopters. Chief among these is the challenge of scale, often reflected in limitations of concurrency, multi-tenancy, distributed query performance, and all manner of latencies. Other less obvious, but equally crucial, challenges of scale and performance have to do with IT and end-user productivity. In other words, there have been few technological advances that enable the quick deployment of big data analytics and the rapid creation of business value from the data being analyzed. This presentation will consider a few of these systemic challenges and suggest some ways that they can be addressed with available open source technology such as Apache Kylin, Apache Spark, and Apache Mondrian. Talk #2: Accelerating Linux Workload Onboarding Experience on Azure Whether you run Linux or Windows, Azure has unlimited capacity to deliver tangible benefits with built in security, hybrid infrastructure, data analysis and intelligence to support your Linux and Open Source Software (OSS) workloads. Our partnership with companies like Kyligence is one of our key strengths. In this talk, we will talk about how Azure supports the OSS ecosystem, and how it empowers customers and partners to build their solutions on Azure.
Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (45)
Subscribers (1284)
Tips and technology walkthroughs you can use to supercharge big data analytics across your organization on any BI tool and any size dataset. Learn how to help your business quickly make data-driven decisions with confidence.