If you’re in the same boat as most organizations then your data warehouse is the main hub for reporting and business analytics. It is likely that you also store massive amounts structured and unstructured information into your data lake, which can be used in machine learning and AI use cases. It’s time to upgrade to a modern data platform. With an outdated infrastructure and rising costs, it is time to consider a cloud data platform.
To find the ideal solution, you have to take into consideration your company’s long-term strategy as well as current business requirements. One of the most important aspects to consider is architecture, platform and tools. Are an enterprise-grade big data room data store (EDW) or a data lake that is cloud-based most suitable for your needs? Use extract, transform and loads (ETL) or a source-agnostic layer of integration? Do you wish to use a managed cloud service or set up your own data warehouse?
Cost: Look at pricing models, and compare factors like compute and storage to ensure your budget is aligned with your needs. Select a vendor that has a cost structure that supports your short, midand long-term data strategy.
Performance: Consider the current and projected volume of data and the complexity of queries to determine if you want an appropriate system that can support your initiatives based on data. Choose a vendor who offers flexible data models that can adapt to your business growth.
Programming language support: Ensure that the cloud software for data warehouse you choose has the programming language you prefer, especially if you plan to use the software for testing, development or IT-related projects. Choose a vendor who also provides data handling services like data discovery, profiling, data compression, and efficient data transmission.