A strong data foundation is key for improving decision-making capabilities and supporting AI/BI initiatives, and our warehouse technology was specifically created with this in mind. No need for complex management techniques here, our integrations allow customers to efficiently handle even complex analytics and BI use cases.
Customers also have the flexibility of running their data warehouse on any cloud they choose with either self-managed SaaS or fully managed SaaS options. IBM DB2 Warehouse and Netezza Performance Server SaaS deployments are offered through IBM Cloud and AWS respectively.
Enterprise Data warehouses serve two functions. First, as historical archives to consolidate all necessary business data from various sources, and second as query processing engines which enable business users to interact directly with database content without temporarily pausing database update operations for complex analytical queries to run successfully.
Data errors and gaps arise as a result of frequent interruptions within transactional databases. Data warehouses serve to aggregate information from multiple sources for analytics across them while still permitting databases to focus on performing their transactional duties uninterrupted by interruption.
Data warehouses allow companies to make predictions and increase productivity by consolidating information for analysis. Data warehouses are relational databases typically housed on servers within enterprises. Cloud-built and hybrid cloud data warehouses have also become more and more prevalent as businesses look for solutions that enable them to quickly scale computing resources up or down according to changing volume or concurrency requirements.
Cloud data warehouses make data more readily accessible for organizations by bypassing ETL processes, making data more readily ingested into relational SQL views than ever. Cloud-based solutions allow businesses to quickly analyze and share disparate sources of information at scale in today's age of mobile and IoT devices.
