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Choosing a Cloud Data Warehouse

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If you’re in the same boat as most organizations, then your data warehouse is the primary point for reporting and business analytics. You likely also load massive amounts structured and unstructured information into your data lake, which can be used in machine learning and AI use cases. With aging infrastructure, rising costs and growing demand, it’s time for you to think about upgrading to a modern cloud 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 consideration is the architecture, platform and tools. Are an enterprise-grade data store (EDW) or cloud-based data lakes most suitable for your needs? Make use of extract, transform and loads (ETL) or a scalable source-agnostic layer for integration? Do you plan to set up a cloud-based data warehouse yourself or make use of a managed service?

Cost Pricing: Review www.bigdataroom.info/how-to-secure-your-data-best-recommendations/ pricing models and analyze factors like storage and compute to ensure that your budget is in line with your usage. Select a company with an appropriate cost structure that is compatible with your short-, midand long-term data strategy.

Performance: Evaluate the current and projected volume of data and the complexity of queries to select a system capable of supporting your data-driven initiatives. Choose a vendor that offers an extensible data model that is flexible enough to change as your business expands.

Programming language support: Ensure that the cloud data warehouse software you choose will work with your preferred coding language particularly if you are planning to use the software for development, testing or IT projects. Choose a vendor who offers data handling services including data profiling and discovery, data compression, and efficient data transmission.

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