Analytics

By centralizing processes and reimagining the role of its analysts, Calix’s data team found that it could deliver more value faster.

Some of the most forward-operational elements of the United States federal government are making strides in leveraging data through hybrid cloud environments—and they’re constantly evaluating progress and recalibrating their approaches along the way. At agencies including the Army and the State Department, work is well underway to find ways of employing emerging technologies that build on cloud services and data optimization to realize new levels of effectiveness.

BigQuery is Google's flagship data analytics offering, enabling companies of all sizes to execute analytical workloads. To get the most out of BigQuery, it’s important to understand and monitor your workloads to keep your applications running reliably. Luckily, with Google’s INFORMATION_SCHEMA views, monitoring your organization’s use at scale has never been easier. Today, we’ll walk through how to monitor your BigQuery reservation and optimize performance.

Working in the engineering field means navigating a variety of needs. Those range from meeting various local and national regulatory statutes, to measuring and monitoring delivery of essential outputs like drinking water and power supply, to understanding the data surrounding regional operations on both the supply and demand side. Organizations that serve this market operate behind the scenes, yet impact our daily life in the United States.

Chances are, your data contains information about geographic locations in some form, whether it’s addresses, postal codes, GPS coordinates, or regions that are meaningful to your business. Are you putting this data to work to understand your key metrics from every angle? In the past, you might’ve needed specialized Geographic Information System (GIS) software, but today, these capabilities are built into Google BigQuery.

A quick and easy way to speed up small queries in BigQuery (such as to populate interactive applications or dashboards) is to use BI Engine. The New York Times, for example, uses the SQL interface to BI Engine to speed up their Data Reporting Engine. To Illustrate, I’ll use three representative queries on tables between 100 MB and 3 GB — tables that are typically considered smallish by BigQuery standards.