JOIN 2017: 5 Things You Don't Want to Miss
The goal for JOIN is simple: Provide an intimate environment where smart data people can meet each other, mingle with our Looker team and walk away feeling like they actually learned something.
Query Exabytes of Data in AWS with Looker’s Native Support of Amazon Redshift Spectrum
Looker natively supports Amazon Redshift Spectrum, which allows users to analyze exabytes of data stored in S3 without having to load it into Redshift first. Spectrum will allow Looker users to dramatically increase the depth and breadth of the data that they are able to analyze in Redshift.
Finance: How we Looker at Looker
Looker is growing very quickly. While our growth is dramatic, our ability to scale using Looker may be best demonstrated (in my not-so-humble opinion) by the Looker Finance Department.
Using New York City Taxi Data to Avoid Airport Traffic
Yellow cabs are as iconic as the NYC skyline. They're known for being fast—and a little bit scary. But is there a best time to hail a cab in NYC? We decided to explore NYC Taxi Data to find out.
5 Tips to Becoming a Data-Driven Marketer
Most people can pull up a pretty visualization or a create a wonderful presentation with numbers. But as a marketer, and also someone who has taken advanced statistics courses, numbers are meaningless unless you trust and understand the metrics behind them.
Culture Comes from the Inside Out, not the Outside In
Looker was recently announced as the #3 mid-sized company and #1 mid-sized tech company on the Silicon Valley Business Journal’s 2017 Best Places to Work list. When people ask me about what makes Looker so special, they often want to know about our perks.
Elastic Analytic Databases
Increasing data volumes, the need to support huge numbers of users, and the advent of the cloud has paved the way for a new class of database. These “Elastic Databases” open up entirely new frontiers in what is possible with analytics.
Invest in your Most Valuable Asset with HR analytics
Modern marketing organizations utilize multiple tools to execute and track campaigns. However with so many different data sources, it can be difficult to get a holistic view of marketing’s influence on opportunity conversion and revenue generation. The Looker Block for Campaign to Cash Analytics brings in data from Marketing systems and Website/Social Marketing systems, and ties them together into a single central warehouse to allow users to gain insight from a blended data spectrum.
Data Science with Looker: Part II
To show how seamlessly Looker can integrate into a data science workflow, we took a public dataset (Seattle bikeshare data) and applied a predictive model using Looker, Python, and Jupyter Notebooks. Follow along as I walk through the setup.
Data Science with Looker: Part I
Data scientists spend most of their time in a dedicated Data Science Environment (DSE) but only a small portion of their time is actually spent on advanced analytics. Read more to learn how Looker can make the Data Science workflow more efficient.