If you’re in the same boat as most companies your data warehouse is the central point for crucial business analytics and reporting. It is likely that you also store massive amounts structured and unstructured information into your data lake to be used in machine learning and AI applications. With an old infrastructure, rising costs and an increasing demand, it’s time for you to look into upgrading to a more modern cloud-based data platform.

It is important to consider the current needs of your business and long-term plan when selecting the right solution. A key consideration is the architecture, platform and tools. Will an enterprise data store (EDW) or a data lake that is cloud-based best meet your needs? Make use of extract, transform and loads (ETL) or a flexible layer of source-agnostic integration? Do you want to build an on-premise cloud data warehouse or employ an managed service?

Cost Pricing: Review pricing models and compare factors such as storage and compute to ensure that your budget is in line with your needs. Choose a provider with a cost structure that supports your short-, midand long-term strategy for data.

Performance: Examine the present and anticipated data volumes and complexity of queries in order to select the best system for your initiatives based on data. Select a vendor with a scalable data model, with the ability to change as your business grows.

Support for programming languages: Ensure that the cloud data warehouse software you select will work with your preferred coding language especially if you intend to utilize the product for testing, development or IT projects. Choose a provider that offers data handling solutions, such as view it now data profiling, discovery, data compression, and efficient data transmission.