Cloud adoption is accelerating, alongside automation, offering companies a path to increase their database capabilities in ways not possible before.
Reducing infrastructure costs, improving systems agility, and supporting new use cases are all key drivers. Moreover, since heterogeneity still rules the day at most enterprises, it's no surprise that hybrid, multi-cloud architectures are quickly becoming the go-to strategy.
At the same time, the challenges of managing, governing, securing and integrating data are growing in step as data environments continue to expand in size and complexity—and new database skills and solutions are absolutely required.
DBTA held a roundtable webinar with Lenore Adam, director of product marketing, Delphix; Deji Akomolafe, staff solutions architect, VMware; and Lewis Carr, senior director, product marketing, Actian, who discussed how to survive and thrive in the cloud era.
Data bottlenecks plague DevOps pipelines, Adam said. Data distribution and security can’t keep pace with DevOps workflows or a complex data ecosystem. Data is the slowest component of the app dev value chain. It is difficult to maintain compliance in cloud-based test environments. According to a Pulse Survey, Jan 2021, 81% of respondents found it difficult to maintain data security and compliance in cloud-based test environments.
Additionally, 56% of respondents said sensitive data is not anonymized for use in test environments. Data in non-production environments is not secure enough.
This is where Delphix comes in, Adam explained. The Delphix Data platform provides a programmable data infrastructure.
The solution offers data virtualization, compliance, is API-first, provides data as code, has multi-cloud sync, and immutability.
“The cloud” is a destination for “most important” workloads, Akomolafe said. He recommended organizations support scenarios and options.
“Your on-premises support contracts do not necessarily extend to your public/hybrid cloud workloads,” Akomolafe said.
According to Carr, there are three data management trends in the cloud era that include:
- Cloud introduces new data silos
- Cloud Data Warehouses will focus convergence and redesign of on-premise hubs, lakes, and warehouses
- Cloud removes business user disintermediation
Organizations are struggling to extract real-time insights from their data analytics, he said. According to Carr, 80% of their time and resources is spent on data prep and quality—not insights.
The next generation of cloud data analytics needs to include a real-time connected data warehouse that provides batch and streaming modes; connect to and ingest from diverse and disparate data sources; offers data preparation and quality; self-service data access and preparation for non-IT users; eliminates spreadsheet silos; offers advanced analytics (canned and customized); can do advanced analytics with Spark, Kafka, and other open standards; offers cost-effective scale; semi-structured data, and more.
An archived on-demand replay of this webinar is available here.