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Choosing a Cloud Data Warehouse

If you’re similar to the majority of organizations, then your data warehouse is the primary point for reporting and business analytics. It is likely that you also store massive amounts structured and unstructured data into your data lake to be used in machine learning and AI applications. It’s time to upgrade to a more modern data platform. With an outdated infrastructure and rising costs, it is time to think about the cloud data platform.

You must take into account your organization’s current business needs and long-term strategy when choosing the right solution. The architecture, platform and tools are all important aspects to consider. Are an enterprise-level data warehouse (EDW) or cloud-based data lakes best meet your needs? Should you choose to use extract transform and load (ETL) tools or an easier to use source-agnostic integration layer? Do you prefer to use a managed cloud service or even build your own data warehouse?

Cost: Evaluate pricing models, comparing variables like compute and storage to ensure your budget is aligned with your usage. Choose a vendor with an expense structure that fits your short, mid- and long-term data strategy.

Performance: Assess current and projected data volume and query complexity to select a system that can help you with your data-driven projects. Select a vendor with an scalable data model that can be adapted to the growth of your business.

Support for programming languages Be sure that the cloud data big data room warehouse software you choose supports your preferred coding languages especially if you intend to use the software for development, testing or IT projects. Choose a provider that offers data handling solutions, such as data profiling and discovery, data compression and efficient data transmission.

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