With Kafka, CoolaData ensures that our resources consume and process billions of messages without losing any data along the way. We’re able to monitor our system for peaks, as well as increase the amount of resources that we provide for data processing. It also enables us to safely deploy new features and fixes without losing or delaying customer data.
CoolaSQL’s proprietary extensions allow users to use SQL syntax to jump-start user behavior analysis, including user paths, cohorts, and funnels, while CoolaData performs non-relational database operations internally. For instance, as shown below, analysts can execute user path queries, find patterns in application usage and group by similar user patterns behind the scenes. This way analysts receive query result sets in an organized, relational manner.
Acquire, Convert and Retain Fashion eCommerce Customers. Manipulate data so that it can bring the right customer to the site or app. Data provides insights about where the customers came from: Are they organic? Did an existing customer bring them to the store? Knowing where new traffic comes from and how much was paid for it is key to allocating future customer acquisition funds accordingly and boosting future traffic.
CoolaData is offering the following webinars this month… All our webinars are live and we take time for an extensive Q&A session at the end. We look forward to seeing you online!
In this blog post we will unveil the true cost of building a Big Data analytics solution. The expenses are divided to three main categories: infrastructure, software and human resources, the latter being the most demanding.