David Menninger's Analyst Perspectives

Organizations conduct data analysis in many ways. The process can include multiple spreadsheets, applications, desktop tools, disparate data systems, data warehouses and analytics solutions. This creates difficulties for management to provide and maintain updated information across multiple departments. Our Analytics and Data Benchmark Research shows that organizations face a variety of challenges with analytics and business intelligence. One-third of participants find it difficult to integrate analytics and BI with other business processes. Participants also find that not all software is flexible enough for the constantly changing business environment, and that it is hard to access all data sources.

Oracle Analytics Cloud is a unified platform that enables organizations to run analytics and business intelligence across multiple environments and devices. It can be integrated into an existing ecosystem, allowing users to perform analysis in the cloud while also accessing distributed data sources.

Oracle provides IT products and services for various enterprise environments, including applications and infrastructure offerings and interoperable IT deployment models that support on-premises, cloud and hybrid deployments. Oracle Analytics Cloud is an Oracle-managed service built on the Oracle cloud infrastructure. It provides capabilities to explore and perform collaborative analytics, and offers flexible service management capabilities including fast setup, easy scaling and patching and automated life cycle management. It supports analytics workflows, including data connectivity, data preparation, data flow, data modeling, visualization, discovery and collaboration. The analytics capabilities benefit various users, including IT practitioners, executives, data engineers, citizen data scientists, analysts and business users. Using REST application programming interfaces, workers can automate processes and programmatically access features and functionality.

Oracle Fusion Analytics is a suite of prebuilt, cloud-native analytic applications that offer ready-to-use insights for quick decision-making. It provides a code-free environment for teams in HR, finance, procurement and operations to enrich analytics efforts using embedded machine learning and additional data from other sources beyond Oracle Cloud applications. Oracle’s combined analytics and application capabilities enable organizations to unify analytics and create a consolidated view of performance across departments.

Oracle Analytics Cloud was launched in 2019. The Oracle Analytics Summit of 2019 was the inaugural user event for Oracle Analytics customers, and Oracle announced three major new offerings: the Oracle Analytics Cloud, a managed service hosted by Oracle; Oracle Analytics Server, an on-premises version of the same analytics software; and Oracle Analytics for Applications, which is the same analytics technology embedded within applications. It was Oracle's effort to replatform business intelligence products to the cloud.

Oracle recently announced a series of new products across its portfolio of data and analytics applications. It added new capabilities to Oracle Fusion Analytics to support customer experience, enterprise resource planning, human capital management and supply chain management analytics, providing decision-makers with a prebuilt library of more than 2,000 best-practice key performance indicators, dashboards and reports to monitor performance against strategic goals.

The latest innovations are designed to improve the productivity of business users by minimizing reliance on IT while still benefiting from curated data assets created by IT, such as the centralized semantic model. Artificial intelligence and machine learning enhancements extend ML functionality with other Oracle Cloud Infrastructure cognitive services. Oracle Cloud Infrastructure Vision allows users to analyze image-based content in a simple dashboard.

Oracle Analytics enables business users, data engineers and data scientists to access and process data, evaluate predictions and make decisions backed by data. Its next-generation semantic modeler is entirely web based and offers new functionality, including a multi-user developer experience with tight Git integration and a new semantic model markup language to more flexibly edit and update models. I have previously written about semantic models and how they positively affect the success of an organization’s data and analytics processes.

Organizations can use Oracle Analytics to simplify the analytics process, including data ingestion, data preparation and enrichment, and data visualization and collaboration. It has ML capabilities embedded throughout the platform to enable organizations to run various data science and ML projects. Its data preparation and visual data flows with ML capabilities allow users to see the steps to transform and enrich data and then automate them. Its software developer kit enables workers to incorporate custom visualizations and frameworks and embed Oracle Analytics Cloud into other applications and user experiences to incorporate analysis into their daily work. With Oracle Analytics Cloud, augmented analytics, self-service analytics and governed analytics can be combined into a single application that simplifies processes and lowers operational costs.

Oracle is putting great effort into taking all data and analytics processes to the cloud. It should also continue to improve the product experience, making it more adaptable and flexible for various business needs and extending its award winning natural language query capabilities beyond mobile applications to the desktop. I recommend that organizations looking to take analytics and data processes to the cloud with a unified analytics platform offering multiple data analytics and BI capabilities consider Oracle Analytics Cloud.

Regards,

David Menninger