If you’re like the majority of organizations your data warehouse is the central center for reporting and analytics. You likely also load massive amounts of structured and unstructured data into your data lake, which can be used for machine learning and AI applications. It’s time to upgrade to a modern data platform. With aging infrastructure and rising costs, it’s time to think about a cloud data platform.
To find the right solution, you need to consider your organization’s long-term plan and current business requirements. The architecture, platform and tool set are crucial aspects to consider. Are an enterprise-level data warehouse (EDW) or cloud data lake best suit your requirements? Do you need extract transform and load (ETL) tools or a more flexible source-agnostic integration layer? Do you wish to use a cloud-based service that is managed or set up your own data warehouse?
Cost: Evaluate pricing models, comparing variables like storage and compute, to ensure that your budget is aligned to your needs. Choose a vendor whose cost structure supports your short, medium and long-term data strategies.
Performance: Consider current and projected data volume and query complexity before deciding on the right system to support your data-driven initiatives. Select a vendor that has the ability to scale data models, that is flexible enough to change to the growth of your business.
Programming language support Be sure that the cloud software for your data warehouse supports your preferred coding languages particularly if you are planning to use the software for testing, development or IT-related projects. Select a vendor that provides data handling services like data discovery, profiling, as well as data compression and efficient data transmission.