Webinar Abstract
Putting data into a database and getting it back out are surprisingly different operations, despite the fact that both rely heavily on the capabilities of a vendor’s database management system (DBMS). Because these are two distinct “database workloads,” the common approach for many years has been to provide separate DBMS instances and server/storage hardware for application databases and data warehousing, each instance modeled and optimized for its primary workload. Yet, there are good reasons why some user organizations should consider consolidating the two database workloads onto a single database platform.
For example, the integration of operational applications and data warehouses is one of fastest growing technology practices today, because it enables business practices like operational business intelligence, performance management, and zero-latency enterprises. As another example, the consolidation of sensitive data into fewer silos simplifies growing organizational practices, like governance, compliance, security, and data privacy. Some data management practices are likewise simplified, like data integration, data quality, master data management, and metadata management. And, in many organizations, packaged operational applications and data warehouses are sponsored and funded by the same organizational body, so it makes sense to combine their data onto a single database platform owned by that body.
You will learn:
- Business and technology situations that would benefit from workload consolidation for transaction processing and business intelligence
- How business requirements and technology capabilities have changed recently, making the consolidation of mixed workloads more imperative and likely to succeed
- Synergies between database workload consolidation and practices like operational business intelligence, operational data warehousing, real-time or on demand computing, data governance, compliance, analytics/reporting embedded in operational applications, and so on
- The hefty technology requirements for a single database platform that can support diverse workloads simultaneously with scalability and high performance
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