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If you’re like most organizations your data lake is an important hub for reporting and business analytics. You likely also load huge amounts of unstructured and structured data into your data lake to 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.

You must take into account your company’s current business requirements and long-term goals when selecting the right solution. A key consideration is the architecture, platform and tools. What kind of enterprise data store (EDW), or cloud-based data lakes best meet your needs? Should you bigdataroom.info/how-to-secure-your-data-best-recommendations use extract transform and load (ETL) tools or a more flexible source-agnostic layer? Do you wish to use a cloud service managed by a company or build your own data warehouse?

Cost Comparing pricing models and compare factors like compute and storage to ensure that your budget is in line with the amount you use. Choose a provider with the cost structure that will support your short, midand long-term strategy for data.

Performance: Evaluate the volume of data currently and in the future and query complexity to choose the best system to assist your data-driven initiatives. Select a vendor with a scalable data model, that can be adapted as your business grows.

Support for programming languages: Make sure the cloud data warehouse software you select is compatible with your preferred programming languages particularly if you intend to utilize the product for development, testing or IT projects. Select a vendor that offers data handling services like data discovery and profiling, data compression and efficient data transmission.