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This Month In Data Science: November 2015

With the Presidential race heating up, the increasing importance of data science within the candidates’ campaigns received attention in November. In other news, Stanford's School of Engineering held the first Women in Data Science conference, the National Science Foundation invested in cross-disciplinary data science partnerships, and the discipline’s capability to track and explain global consumer trends was focused on. Here’s our roundup of the biggest data science news of the month, both from Pivotal and beyond.

Data, Why Did It Have To Be Data?

In this episode, host Coté once again chats with Andrew Clay Shafer about the sundry challenges of transforming to a Cloud Native enterprise. They cover the changing focus we're seeing among Pivotal customers: moving up the stack from infrastructure to the application layers. Then they discuss the difficulties of handling the data layer, and wrap-up with some change management tactics for getting the "rank and file" inspired and bought into the Cloud Native lifestyle.

Build Newsletter: Dell, Our Big Data Promise, Unicorns & More—Nov 2015

Welcome to the November 2015 edition of the Build Newsletter. For this edition, we start out with the big Dell acquisition news, talk about our donation of 5 million lines of code to open source, discuss unicorns and disruption, and provide a huge list of Cloud Native development updates.

All About The New Open Source Greenplum Database

It is an exciting time for customers using data-related software—with more data being processed an analysed than ever. To do this effectively you need some heavy duty technology. And one of the best for a long time has been the Pivotal Greenplum Database. Now, this database is available as open source—giving customers even more flexibility, and enabling a flourishing community of developers and contributors. In this episode, host Simon Elisha explores more about what this means and how you can be a part of it.

This Month In Data Science: October 2015

The promise and risks of big data analysis received attention of scrutiny in recent weeks. While data science’s ability to optimize performance and facilitate more effective operations was seen in the oil and gas, shipping, and even restaurant industries, the risk that “algorithmic bias” will enforce existing social inequities received serious scrutiny. Here’s our roundup of the biggest data science news of the month, both from Pivotal and beyond.

Multivariate Time Series Forecasting for Virtual Machine Capacity Planning

In this blog, we continue our blog series on multivariate time series to apply this modeling approaches for forecasting virtual machine capacity planning. This technique can be broadly applied to other areas as well such as monitoring industrial equipment or vehicle engines.

Forecasting Time Series Data with Multiple Seasonal Periods

Time series data is produced in domains such as IT operations, manufacturing, and telecommunications. Examples of time series data include the number of client logins to a website on a daily basis, cell phone traffic collected per minute, and temperature variation in a region by the hour. Forecasting a time series signal ahead of time helps us make decisions such as planning capacity and estimating demand. In this post, Anirudh Kondaveeti examines the modeling steps involved in forecasting a time series sequence which includes multiple seasonal periods.

Introducing Spring Cloud Data Flow

Large-scale online service architectures for enterprise applications have been validated this year, through the use of composable microservices on a structured platform. The most powerful and successful products for continuous delivery of these applications are the Pivotal Cloud Native stack, which includes Spring Boot, Spring Cloud, and Pivotal Cloud Foundry. Pivotal has continued to define and refine the Pivotal stack to bring the benefits of our structured platform to the full range of development scenarios. To that end, today Pivotal announces Spring Cloud Data Flow: Cloud Native composable microservices for ingesting, transforming, storing, and analyzing data.

Christian Tzolov on Open Source Engineering, the ODP and Pivotal

Christian Tzolov has worked on some really amazing projects in his life—artificial intelligence, data science, and big data to name a few. As a big data and Apache Hadoop® specialist on our Field Engineering team, he spends a lot of time working on open source projects and helping customers solve problems. In this post, we get an in-depth Q&A where he shares quite a bit about his work with Apache® BigTop, Apache Ambari, Apache Zeppelin (incubating), Apache Crunch and more.

All About the New GemFire For Pivotal Cloud Foundry Service

This week, Pivotal Perspective's host Simon Elisha take a look at the new GemFire for Pivotal Cloud Foundry Service that is now available and delivering one of the market’s most powerful in memory technologies on Pivotal’s open Cloud Native application platform. In this week's episode, Simon explores what it can do and how you might use it.