If you’re like most organizations your data warehouse serves as the central point for crucial reporting and business analytics. You probably also populate massive amounts of structured and unstructured information into your data lake, which can be used for machine learning and AI use cases. It’s time to upgrade to a more modern data platform. With an outdated infrastructure and rising costs, it’s time to consider a cloud data platform.
To find the right solution, you have to take into consideration your organization’s long-term strategy and the current business needs. The architecture, platform and tool set are crucial aspects to consider. What kind of enterprise data warehouse (EDW) or cloud data lakes best meet your needs? Make use of extract, transform and loads (ETL) or a flexible layer of source-agnostic integration? Do you want to utilize a cloud service managed by a company or set up your own data warehouse?
Cost: Examine pricing models and compare variables like storage and compute, to ensure that your budget is in line with your usage. Select a provider whose cost structure can support your short, mid and long-term data strategies.
Performance: Consider the current bigdataroom.info/how-to-secure-your-data-best-recommendations and projected volume of data and query complexity to select the best system to help you with your data-driven projects. Select a vendor that has the ability to scale data models, with the ability to change to your business’s growth.
Support for programming languages: Make sure that the cloud data warehouse you choose supports your preferred coding language, especially if you intend to use the product for IT projects, development, testing or for other purposes. Choose a vendor who also provides data handling services, such as data discovery and profiling, data compression and efficient data transmission.
