Ethereum: Rise of the World Computer
The Ethereum network is a distributed economy like Bitcoin, except it is much, much more powerful. Rick Seeger dives into why you should be paying attention to its popularity.
Author Archive
Data: What Industry Wants
Since launching Silicon Valley Data Science, we hear three issues more often than anything else in the conversations we have with our clients: handling data overload, choosing analytic approaches, and having the right skills and resources. Let’s take a look at these.
Reshaping Data with Pivot in Spark
Andrew gives you a deep dive into pivoting data with SparkSQL. This piece was originally posted on the Databricks blog.
Data Day and Graph Day Texas Slides
Check out the slides from our recent presentations at Data Day TX and Graph Day.
Space Shuttle Problems: Long-term Planning Amid Changing Technology
How can you manage your implementation in a way that allows you to take maximum advantage of technology innovation as you go, rather than having to freeze your view of technology to today’s state and design something that will be outdated when it launches? You must start by deciding which pieces are necessary now, and which can wait.
Data Strategy in a World of Big Data
Silicon Valley Data Science has designed a new method to create a data strategy that overcomes limitations of conventional approaches. Recent advances in communications, networking, data, and analytics technologies are changing the way leading companies organize around, architect for, and deliver data-driven capabilities.
The “Why?” Behind a Modern Enterprise Data Strategy
Scott Kurth, John Akred, and Julie Steele discuss developing a modern data strategy during an Ask Me Anything at Strata NY 2015. This was originally posted on the O’Reilly Media Data blog.
Pivoting Data in SparkSQL
Andrew Ray, Senior Data Engineer, contributed to the most recent release of Spark. This post gives examples of how to use his pivot commit in PySpark.
Getting Value Faster with a Data Strategy
Companies that demand immediate technical results often don’t want to take the time to develop a data strategy up front, but it will actually accelerate business value for your company. In this post, I’ll describe how these components fit together and work to bring you business value quickly.