Choosing a Cloud Data Warehouse

If you’re in the same boat as most companies your data warehouse serves as an important hub for reporting and business analytics. It is likely that you also store huge amounts of unstructured and structured information into your data lake, which can be used for machine learning and AI applications. With an outdated infrastructure, rising costs and an increasing demand, it’s time for you to look at upgrading to a new cloud data platform.

You should consider the current needs of your business and long-term goals when selecting the best solution. The most important thing to consider is architecture, platform and tools. Will an enterprise data store (EDW), or a cloud-based data lake, most suitable for your needs? Utilize extract, transform, and loads (ETL) or a source-agnostic layer of integration? Do you intend to create a cloud-based data warehouse yourself or employ an managed service?

Cost: Compare pricing models and other factors like storage and compute to ensure that your budget is in line with your needs. Select a vendor that has a cost structure that supports your short-, mid-and long-term strategy.

Performance: Examine the data volumes and query complexity to select an appropriate system that can support your data-driven initiatives. Select a vendor that offers an adaptable data model that is able to adapt to your business growth.

Support for programming languages: Make sure that the cloud data warehouse you select is compatible with your preferred programming language, especially if plan to use the product for IT projects, development, testing or for any other purpose. Choose a vendor that also provides data handling services, including data profiling and discovery, data compression and efficient data transmission.

Deja una respuesta

Tu dirección de correo electrónico no será publicada.