Systems | Development | Analytics | API | Testing

Gravity Digital needed a more transparent reporting tool to improve communication with its clients and across its internal team.

We dare you to go to your mobile device and search for a health and wellness app already installed. Truth is, even if you did not actually download it, your operating system most likely came with at least one app like that. Now, you might have chosen to delete such an app, in which case, we lost the dare. But it does not deny the fact that your mobile device, the very one that lets you shop, communicate, work, or travel, has just as much potential to assist in your well-being.

As the owner of Analytics, Monetization and Growth Platforms at Yahoo, one of the core brands of Verizon Media, I'm entrusted to make sure that any solution we select is fully tested across real-world scenarios. Today, we just completed a massive migration of Hadoop and enterprise data warehouse (EDW) workloads to Google Cloud’s BigQuery and Looker.

Extract, Transform, Load technology sits between your data source and its destination in your data stack. It’s a useful way of delivering data from multiple applications, databases, and other sources to your CRM, data lake, or data warehouse for analysis and use. But how do you know that it’s time to add ETL to your organization’s data stack?

According to a recent press release by the National Retail Federation, “nearly seventy-three percent of consumers celebrating Valentine’s Day this year feel it’s important to do so given the current state of the pandemic.” The release also states that “consumers still feel it’s important to spoil their loved ones in light of the pandemic.” We couldn’t agree more on the importance of celebrating the day.

Logs are automatically-generated records of events that take place within a cloud-based application, network, or infrastructure service. These records are stored in log files, creating an audit trail of system events that can be analyzed for a variety of purposes, including: Enterprise organizations use log analytics software to aggregate, transform, and analyze data from log files, developing insights that drive business decisions and operational excellence.

When Kudu was first introduced as a part of CDH in 2017, it didn’t support any kind of authorization so only air-gapped and non-secure use cases were satisfied. Coarse-grained authorization was added along with authentication in CDH 5.11 (Kudu 1.3.0) which made it possible to restrict access only to Apache Impala where Apache Sentry policies could be applied, enabling a lot more use cases.

With automation becoming more user-friendly and streamlined than ever before, it's understandable organizations across sectors are examining how it can enhance their analytics capability and accelerate their business shift toward digital transformation.