Improve sales performance and operational efficiencies with better management of incentive compensation plans and smarter administration of sales territories and quotas. Get faster insights with advanced analytics.
Moving on-premises legacy data and analytics workloads to the cloud is unavoidable if you want to overcome infrastructural constraints, facilitate proactive analytics, and lower costs.
You need a service that enables seamless scalability for petabyte-scale data processing, interactive analytics, and machine learning. However, end-to-end, automated workload transformation and optimization on serverless services is not straightforward.
It’s no secret that trust provides a competitive advantage, with trusted companies outperforming their market peers. Boards, executives, and businesses across the globe want to find ways to build trust with consumers, employees, investors, and all stakeholders. But how do you define metrics, quantify, and measure trust?
It can be difficult to scale out relational databases and provide more schema flexibility, thus the rise of NoSQL. However, you shouldn’t have to sacrifice data integrity and transactions in order to scale out on commodity hardware and support semi-structured data. By using an RDBMS with built-in sharding and JSON support, you don’t have to. You get the scalability and flexibility of a NoSQL database along with the consistency and reliability of a relational database – and the ability to mix and match relational and JSON data. In this webinar, we’ll explain how MariaDB Platform can be deployed as a NoSQL database by using the Spider storage engine and built-in SQL functions for JSON. In addition, we’ll discuss how you can access relational data as JSON documents, and how to enforce data integrity if a relational data model is extended with JSON