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Interview: Steven McMullen, Senior Business Intelligence Manager at Stack Overflow

I recently caught up with Steven McMullen, Senior Business Intelligence Manager at Stack Overflow, to discuss how his company tapped pre-IPO data analytics unicorn, Looker to modernize their marketing ops, acquire new leads and new customers. The business results were impressive, transforming Stack Overflow’s marketing strategy for the better.

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

Three Reasons In-Cluster Analytics is a BIG DEAL

Recent technology advances within the Apache Hadoop ecosystem have provided a big boost to Hadoop’s viability as an analytics environment.
You have a lot of data in Hadoop and you’re looking to analyze it. You don’t have to continue bumping up against the limits of the database you’re moving the data into—or how much of it you can afford to use. This whitepaper addresses how you can leverage the power of the cluster you already have in place, expanding and accelerating what you can do while saving you time and money. This is a big deal, it meets a huge demand, it shows how rapidly the technologies have evolved and it delivers on one of the most significant unmet promises of big data analytics.

Embedded Analytics: Beyond Build versus Buy

Embedded Analytics has officially arrived: more and more businesses are looking for a way to provide embedded analytics solutions for their customers. If you are considering doing this you have several things to consider. Do you build it yourself? Do you purchase a data platform that will do it for you?

In this paper, we offer you several ideas as you consider your project.
– Time to market
– Return on investment
– Organizational fit
– Customization and adaptability

Interactive Analytics, Visualization and Data Modeling on large Hadoop Data Sets

The vision of Hadoop as more than a data store is finally a reality. Thanks to advances from SQL query engines like Spark SQL, Impala, Presto and Hive on Tez, big data technologies are now accessible for business analytics. With Looker, analysts can build a data model across all their data in Hadoop – easily transforming raw data into meaningful metrics and finally allowing business teams to access and explore years of stored data in Hadoop data sets.

Overcome analytic challenges on Hadoop data:

Get more from your Hadoop cluster by analyzing the data where it sits
No need to move or transform the data prior to performing analysis
Interact with your data through a familiar language – SQL on Hadoop
Create a single source of truth for your enterprise that’s governed by a data model
To learn more download this white paper.