Mobile DevOps & Analytics
Wednesday, August 3, 2022
For years, mobile testing has lacked a proper structure and framework to successfully enable development teams to implement and scale continuous end to end mobile testing. After working with hundreds of mobile application companies in his role as co-founder & CTO of Waldo, Laurent Sigal will take you through the guiding principles and practical steps necessary to establish a mobile testing pyramid to shift mobile testing left. Join this session to learn:
-An overview of the mobile testing pyramid that enables mobile teams to break the speed versus quality dichotomy
-How to properly set up your environment to enable end to end testing, including the importance of proper state management
-The six major benefits you will gain from improving your mobile DevOps
The ability to analyze data has long been thought of as a thing you do at your computer. But in this talk we share taking insights from easy-to-use consumer products like Facebook, Linkedin and Robinhood it is possible to take complex query-writing and reimagine interfaces to work for people on their mobile devices.
We'll cover the complexities in handling long running queries on intermittent mobile connections, work required to optimize queries for display on mobile, and show a live demo of how all this works together to make it possible for everybody - from developers to truck drivers to use data wherever.
As cities and towns across the country continue to grow, traffic, congestion, and the lack of parking are becoming more common. Although improving infrastructure, investing in roads, and adopting common sense policies can help alleviate the problem—in our day and age, technology can be a crucial tool in our efforts to address these challenges. How can machine learning facilitate commutes across the country while making our country’s roads more efficient? In the same breath, how can we help local municipalities tackle the challenges of outdated infrastructure and modus operandi? By using various data sets—from weather, traffic, and parking—machine learning is a crucial tool in unlocking our country’s roads for more efficient rides and overall smooth road experiences. These data points, along with the strengths of machine learning, have the potential to empower local governments across the country to address the challenges they face in terms of intra-city transportation. Likewise, the key to adopting policies that benefit commuters and citizens lies within these learnings. Creating efficient roads and setting riders free is possible by collecting key data and machine learning.