If you’re in the same boat as most companies the data warehouse is your primary center for reporting and analytics. You probably also add massive amounts of structured and unstructured data into your data lake to 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 With an outdated infrastructure and increasing costs, it’s time to think about a cloud-based data platform.
You must consider your company’s current business requirements and long-term strategy when www.bigdataroom.info/ choosing the best solution. A key consideration is the architecture, platform and tools. What kind of enterprise data store (EDW) or a data lake that is cloud-based best suit your needs? Should you use extract transform and load (ETL) tools or a more flexible, source-agnostic layer? Do you wish to use an managed cloud service or deploy your own data warehouse?
Cost Comparison of pricing models and evaluate factors like compute and storage to ensure that your budget is compatible with your requirements. Choose a provider with an expense structure that fits your short-, midand long-term strategy.
Performance: Assess the present and anticipated data volumes and complexity of queries in order to select the right system to support your initiatives based on data. Choose a vendor who offers a flexible data model that is able to adapt to the needs of your business.
Support for programming languages: Make sure that the cloud data warehouse you choose can work with your preferred coding language, especially if intend to use the product for IT projects testing, development, or for any other purpose. Choose a vendor who offers data handling services, such as data profiling and discovery, data compression and efficient data transmission.