Rosendin modernizes data and streamlines their workforce with Autonomous Database
December 15, 2023 | 5 minute read
Authored by Laura McKechnie, director of business development for Oracle Cloud solutions at Oracle, and Kellsey Ruppel, principal product marketing director at Oracle.
Figure 1: Rosendin leads the industry by using innovative technology to do jobs faster, safer, and with more efficiency.
Rosendin Electric is a $3 billion, employee-owned US company with offices located nationwide. They have been trusted for more than 100 years of building and maintaining quality electrical and communications installations for commercial and consumer markets. They’re renowned for maintaining good customer and partner relationships.
Challenges of data and analytics at Rosendin
Rosendin was experiencing high maintenance overhead from database administrators and developers, and their outdated Oracle Business Intelligence Enterprise Edition (OBIEE) implementation wasn’t fulfilling user needs. It was also hard to onboard new business use cases, identify new data sources, and performance was very poor. The quality of their data was also poor, which led ultimately to poor decision-making, impacting the business and business operations. Finally, Rosendin’s physical servers were reaching end-of-life.
Why Rosendin chose Oracle
Rosendin wanted to replace outdated implementations, which weren’t serving their purpose anymore. They also wanted to adopt cloud technology in a shared, maintenance-free environment, so they turned to Oracle Autonomous Database and Oracle Analytics Cloud (OAC). Rosendin chose Autonomous Data Warehouse for its ease and manageability and elasticity of a shared cloud environment of Autonomous Database. Autonomous Data Warehouse was faster, required less maintenance, and allowed Rosendin to retire old hardware. With Autonomous Data Warehouse, they could modify data models easily in multiple ways with multiple users, and it was easy to migrate from Rosendin’s existing Oracle implementation.
Oracle Data Integration was attractive to Rosendin because it provides integrations and scalability with Oracle tools.
With OAC, they rebuilt the OBIEE dashboards with OAC Classic and added visualizations for executives. Rosendin was able to scale this to hundreds of users with different use cases across the company. Oracle Data Visualization provided ease of creating data visualization tools quickly for new business cases, such as install rate dashboards.
“As the essential migration succeeded, and the implementation has matured, Autonomous Database has become the central repository of data, enabling ease of access to data, through multiple tools, making data analysis simple for us, improving operations and saving money for us,” says Cathye Pendley, Business Intelligence manager at Rosendin. “By having the right data model and data available, one of the first new projects we did was to identify $300k in labor inefficiencies with only 10 hours of work. We’re able to pass those savings to work better with our partners. That’s a gamechanger.”
Figure 2: Oracle Modern Data Platform is comprised of cloud products, solutions and services to support the architecture.
Suite of Oracle products used
Oracle Cloud Infrastructure (OCI) includes all the services needed to migrate, build, and run IT in the cloud, from existing enterprise workloads to new cloud native applications and data platforms. Rosendin used the following OCI services and technologies:
- Autonomous Database Serverless: Autonomous Database provides an easy-to-use, fully autonomous database that scales elastically, delivers fast query performance, and requires no database administration. With Autonomous Database Serverless, you don’t need to configure or manage any hardware or install any software. Autonomous Database handles provisioning the database, backing up the database, patching and upgrading the database, and growing or shrinking the database. Autonomous Database is a completely elastic service.
- Autonomous Database Serverless Autonomous Data Warehouse: Autonomous Data Warehouse is a fully automated cloud database service optimized for analytic workloads, including data marts, data warehouses, and data lakes. It’s preconfigured with columnar format, partitioning, and large joins to simplify and accelerate database provisioning, extracting, loading, and transforming (ELT) data, running sophisticated reports, generating predictions, and creating machine learning models.
- Oracle Analytics: Oracle Analytics is a complete platform with ready-to-use services for a wide variety of workloads and data. Offering valuable, actionable insights from all types of data in the cloud, on-premises, or in a hybrid deployment, Oracle Analytics empowers business users, data engineers, and data scientists to access and process relevant data, evaluate predictions, and make quick, accurate decisions.
- Oracle Data Visualization: Data visualization is part of many business intelligence tools and key to advanced analytics. It helps people make sense of all the information, or data, generated today. With data visualization, information is represented in graphical form, as a pie chart, graph, or another type of visual presentation.
- Oracle Data Integrator: Data Integrator is a comprehensive data integration platform that covers all data integration requirements from high-volume, high-performance batch loads to event-driven, trickle-feed integration processes, to service-oriented architecture-enabled data services. Oracle Data Integrator12c, the latest version of Oracle’s strategic Data Integration offering, provides superior developer productivity and improved user experience with a redesigned flow-based declarative user interface and deeper integration with Oracle GoldenGate.
- Oracle E-Business Suite: Oracle E-Business Suite supports today’s evolving business models, drives productivity, and meets the demands of the modern mobile user. Building on a 30-year history of innovation, Oracle E-Business Suite continues to deliver new application functionality and expand the capabilities of existing features while helping you gain all the benefits of OCI.
- Oracle Machine Learning: Machine Learning in Oracle Database supports data exploration, preparation, and machine learning (ML) modeling at scale using SQL, R, Python, REST, automated machine learning (AutoML), and no-code interfaces. It includes more than 30 high performance in-database algorithms producing models for immediate use in applications. By keeping data in the database, organizations can simplify their overall architecture and maintain data synchronization and security. It enables data scientists and other data professionals to build models quickly by simplifying and automating key elements of the ML lifecycle.
Figure 3: A diagram depicting Rosendin’s reference architecture
Summary
Oracle Autonomous Database was initially selected to replace an outdated, high-maintenance data platform and enable new Oracle Analytics and data visualizations for more efficient management of the business. Further, Autonomous Database cloud tools, such as Data Studio, is further enabling ease of data integrations and one-stop-shop access to ML and AI projects in the future.
For more information on Rosendin and Oracle Cloud Infrastructure, see the following resources: