Understanding the data we collect is essential—it allows us to identify trends and uncover answers about our world. However, stories in our data frequently go untold. Large datasets are hard to share between research communities due to their size, security restraints, and complexity. Even if these datasets are accessible to users, the tools needed to query them often require deep technical knowledge.
October happens to be the month to celebrate World Smile Day when Harvey Ball, the inventor of the smiley face declared this day as such to give people a reason to smile. This month, BigQuery users have a lot of new reasons to smile about with the release of new user-friendly SQL capabilities now generally available.
In our latest post we’re covering a range of the different kinds of problems and threats data analysis can help protect your business from. We’ve brought together some of our favourite experts working in big data, cybersecurity and tech to shed light on some of the practical applications of using data analysis for protecting your operations.
Running a large commercial airline requires the complex management of critical components, including fuel futures contracts, aircraft maintenance and customer expectations. Airlines, in just the U.S. alone, average about 45,000 daily flights and transporting over 10 million passengers a year (source: FAA). Airlines typically operate on very thin margins, and any schedule delay immediately angers or frustrates customers.
Apache Spark unifies batch processing, real-time processing, stream analytics, machine learning, and interactive query in one-platform. While Apache Spark provides a lot of capabilities to support diversified use cases, it comes with additional complexity and high maintenance costs for cluster administrators. Let’s look at some of the high-level requirements for the underlying resource orchestrator to empower Spark as a one-platform.
Customers of B2B companies rely on insights from applications to grow their business, secure their infrastructure, make business decisions, and more. Unless your B2B company offers a rich set of analytics within its product, your customers likely demand nightly data dumps from your application so they can analyze application data with their own BI stack.
Virtually every marketing organization is taking steps to become more data-driven, but there are considerable gaps between vision and reality. According to a 2018 Salesforce report, only 47% of marketers have a completely unified view of customer data sources. Meanwhile, customer data complexity is only increasing. According to Salesforce’s 2020 “State of Marketing” study, the median number of data sources leveraged by marketers is projected to jump by 50% between 2019 and 2021.
This spring, Sauce Labs announced the Sauce Testrunner Toolkit (beta) to expand developer-first capabilities and support for native JavaScript frameworks. The Testrunner Toolkit makes setting up, writing, and running web tests easier and faster for developers during early pipeline testing. First it supported Puppeteer, followed by Cypress, TestCafe, and Playwright to provide the flexibility to test the way you want, along with Sauce Labs insights, at scale.
Automation testing has become a recognized domain in the world of software testing. As the name implies, automation testing involves the use of automated tools to carry out test cases with minimal human intervention, then comparing various outcomes and generating test reports. Automated testing is a crucial part of every Agile team to keep up with the demands for fast but high-quality software projects.
