If you’re in the same boat as most companies then your data warehouse is your primary source of reporting and business analytics. You probably also add massive amounts of structured and unstructured data into your data lake, which can be used in machine learning and AI applications. With the aging infrastructure, increasing costs and growing demand, it’s the right time to look into upgrading to a more modern cloud-based data platform.
It is important to consider your organization’s current business needs and long-term strategy when choosing the right solution. The most important thing to consider is architecture, platform and tools. Are an enterprise-level data warehouse (EDW) or cloud data lake best meet your needs? Utilize extract, transform and loads (ETL) or a source-agnostic layer of integration? Do you prefer to use a managed cloud service or set up your own data warehouse?
Cost: Compare pricing models and analyze factors like storage and compute to ensure that your budget is in line with the amount you use. Choose a vendor with an expense structure that fits your short-, middle-and long-term strategy.
Performance: Assess the current and projected volume of data and query complexity before deciding on a system that can assist your data-driven initiatives. Select a vendor that has the ability to scale data models, that can be adapted to the growth of your business.
Programming language support Be sure that the cloud data warehouse software you choose will work with your preferred coding language particularly if you intend to utilize the product for testing, development, or IT projects. Choose a vendor that provides data handling services, such as data discovery and profiling, as well as data compression and efficient data transmission.
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