As data continues to grow at an exponential rate, our customers are increasingly looking to advance and scale operations through digital transformation and the cloud. These modern digital businesses are also dealing with unprecedented rates of data volume, which is exploding from terabytes to petabytes and even exabytes which could prove difficult to manage.
The phenomenon of web-based, at-your-door-in-minutes, restaurant food-delivery service is widespread and commonplace nowadays, with various apps and platforms, such as Grubhub or DoorDash, providing diners with an at-home eating experience – look up a restaurant, choose what you want to eat, and your food is on its way. The same can be said about grocery shopping.
At Singular, we have a pipeline that ingests data about ad views, ad clicks, and app installs from millions of mobile devices worldwide. This huge mass of data is aggregated on an hourly and daily basis. We enrich it with various marketing metrics and offer it to our customers to analyze their campaigns’ performance and see their ROI. The upshot is that we receive tens of thousands of events per second and handle dozens of terabytes of data every day, managing a data set of several petabytes.
Operational Database is a relational and non-relational database built on Apache HBase and is designed to support OLTP applications, which use big data. The operational database in Cloudera Data Platform has the following components: Atlas provides open metadata management and governance capabilities to build a catalog of all assets, and also classify and govern these assets. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets.