Analytics

Five differences between Stitch vs. MuleSoft vs. Xplenty: Organizations of all types need to pull data from disparate locations for data analysis. But the average company draws data from over 400 sources, making data integration difficult. Imagine if a technology could compile data from locations such as in-house databases, cloud-based apps, and SaaS and move it all into a centralized location. Extract, Transform, Load (ETL) makes this possible.

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.

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?