If you’re like many organizations your data warehouse is the central point for crucial reporting and business analytics. It is likely that you also store huge amounts of unstructured and structured information into your data lake to be used in machine learning and AI applications. It’s time to upgrade to a modern data platform. With aging infrastructure and increasing costs, it is time to think about a cloud data platform.
To determine the best solution, you must consider your company’s long-term strategies and current business requirements. The most important thing to consider is architecture, platform and tools. Are an enterprise-grade data store (EDW), or a cloud-based data lake best meet your needs? Utilize extract, transform, and loads (ETL) or a scalable source-agnostic layer for integration? Do you want to use a cloud-based service that is managed or build your own data warehouse?
Cost: Compare pricing models and analyze factors such as storage and compute to ensure that your budget is in line with the amount you use. Choose a vendor whose pricing structure can support your short, mid and long-term data strategies.
Performance: Examine current and projected data volume and query complexity to choose the right system to support your data-driven initiatives. Select a vendor that has an extensible data model with flexibility to adapt to your business’s growth.
Programming language support: Ensure that the cloud software for your data warehouse has the programming language you prefer particularly if you are planning to use the software for development, testing or IT-related projects. Choose a provider that offers data handling solutions, such as data profiling, discovery, data compression and efficient data transmission.
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