The proliferation of the cloud means that data can now be found and extracted from just about everywhere; legacy and cloud-based systems, social media feeds, even email archives. Lots of data equals lots of time spent by businesses trying to manipulate and shape it – of course, the more data available the better, but it can be difficult for businesses to fully utilise their data in order to gain a holistic view of their performance and progress with KPIs.
The traditional approach to building data warehouses is time consuming, incredibly costly and doesn’t lend itself to working with big data or machine learning. Hiring an in-house team of qualified data experts isn’t feasible for most companies, and with tech moving so fast, these companies are in danger of getting left behind. In order to be competitive, businesses simply can’t afford to not be using data and AI to spur growth.
Peak’s AI System gets to work quickly, delivering a comprehensive and unified view of your data in days, not months. Our system is able to automatically build pipelines to stream any type of data, from any source, before bringing it all together into one central database. This can then be further enhanced to include third party data sets and other information sources.
THE TECHIE BIT
Our AI System has been built with business in mind, connecting to all relational databases, cloud platforms such as AWS and Azure, Google Analytics and social media profiles – as well as scraping infinite amounts of data from the web. We bring all of this information together into a single cloud data store within our system and, from there, customers can work directly with their new streamlined data sets or choose to use our other solutions to drive further value.
Building one unified, comprehensive database of key information is something of a golden ticket for businesses. Our solution allows companies to repatriate data from a whole host of cloud services, and de-risks data loss from other platforms. What’s more, we offer businesses better flexibility, enabling end applications to change without a risk of data disappearance.