Once an organization realizes the critical importance of modernizing and future-proofing its data warehouse, the work has just begun. Before a technology partner and platform are selected, it’s vital to understand how to prioritize your requirements.
While every organization has specific challenges and needs that influence how to calculate a data warehouse’s business value, a few requirements are likely to be common to nearly all organizations. These include:
- Enabling more efficient data analytics and application development to meet business needs faster.
- Optimizing database administrators’ and IT staff time so they can focus on strategic initiatives.
- Optimizing the use of resources to reduce the cost of IT operations and infrastructure.
- Increasing revenue from improved business operations.
- Minimizing downtime, which impacts revenue, reduces productivity, degrades the user experience and disrupts critical operations.
Making the best use of internal resources is key to accelerating time to insight and innovation. Traditionally, managing data warehouses has consumed IT’s and database professionals’ valuable time, keeping them from focusing on actions that add more value to the business.
Organizations should adopt a data warehouse that automates manual data management tasks while ensuring uptime and facilitating SecDevOps projects. Such a next-generation data warehouse is likely to be powered by sophisticated machine learning algorithms, freeing up time for database administrators to focus on higher value activities.
Among the key benefits organizations should expect to see when moving to a next-generation, autonomous data warehouse are:
- More productive data analytics processes and teams for better and faster decision-making.
- An increase in database administrators’ productivity.
- Greater agility and ability to support business demands.
- Reduced IT costs.
- Elimination or significant reduction of unplanned downtime.
- Increased productivity of business users, leading to increased revenue.
- Facilitation of an agile SecDevOps development model.
The Real-World Business Value of Oracle Autonomous Data Warehouse
Read this paper to learn the results of a study, conducted by IDC, that sought to learn both the cost savings and business benefits realized by the use of Oracle Autonomous Data Warehouse.
Download NowOptimizing the Value of Data Management With Oracle Autonomous Data Warehouse
Oracle’s decades-long leadership in database management and data warehousing makes it a prime candidate to deliver an intelligent, self-service cloud data warehouse for demanding use cases. Oracle Autonomous Data Warehouse is a cloud data warehouse optimized for high performance, high availability, airtight security, easy scalability and price-performance.
Autonomous Data Warehouse is available both in Oracle’s public cloud and in a customer’s on-premises data center via Oracle Exadata Cloud@Customer. Autonomous Data Warehouse eliminates all the complexities of operating a data warehouse. It automates provisioning, configuration and backup, as well as tasks related to securing, performance tuning and scaling the data warehouse. This reduces administration effort by up to 90%. It additionally includes built-in tools for self-service data loading, data transformation, business modeling and automated insights. Analysts can use graphs and spatial analytics, build machine learning models and create new applications themselves with no-code/low-code built-in tools.
Customers can uniquely combine all necessary data across different sources and formats in a single converged database; DBAs don’t need to manage multiple, isolated, single-purpose databases.
Autonomous Data Warehouse automates data encryption, applies all security patches, and enables threat detection and remediation to protect data.
For more information on calculating the business value of your data warehouse, please refer to this IDC customer study. And try Oracle Autonomous Database for free!
