Typically, when new data or reports are required, IT receives a request from the business. IT then provides data from various sources including enterprise applications, website, external data etc. to the business. IT can also build and run reports and provide insights using this data. After receiving this data from IT, the business function needs time to manually prepare it for analysis and provide access to their team members.
Data security and accessibility issues may arise and by the time they are fixed, some of the data is already outdated. As a result, many stakeholders may ignore the analysis due to a lack of trust in the data, or because their own version of the analysis shows different results.
How Do Data Challenges Impact the Business and IT teams?
Slow: Business demands are constantly growing, but IT resources are limited. This leads to business complaints due to long wait times, and IT can be seen as the bottleneck.
Complex: It involves too many steps and complexity also increases the risk of human errors, and therefore the probability of inaccurate results. Additionally, IT needs to go through this ineffective exercise of providing data extract or reports for each new request they get from LOBs which is not the best use of their time.
Unreliable: It takes time for business analysts to prepare the data and get it ready for analysis. Extracts become stale quickly once exported, which means reports are always behind the actual business state. Spreadsheets often result in human errors, complex reconciliations, and multiple sources of truth, ultimately meaning that insights can’t be trusted, and managers continue making decisions that aren’t data-driven.
Unsecure: Sharing data via files is not secure. Also, some teams may take matters in their own hands and implement shadow IT environments, which increases security risks. According to Gartner, a third of successful attacks experienced by enterprises are on their shadow IT resources.
Incomplete: Business teams lack the ability to deploy machine learning to predict likely outcomes, as well as the ability to use graph and spatial analytics to answer key questions much faster.
Why Oracle Autonomous Data Warehouse?
IT teams might be asked to set up data warehouses for business departments, but they lack the resources needed to manage them on an ongoing basis, and to ensure data governance and security. With Oracle Autonomous Data Warehouse (ADW), IT can significantly improve productivity, performance, and security while reducing costs with an autonomous database.
IDC’s comprehensive business value study based on the real-world experiences of Oracle ADW customers worldwide reveals that ADW offers:
- 417% return on investment
- 63% lower total cost of ownership
- ADW pays for itself in 5 months
Automated Management
Oracle ADW offers automated provisioning, configuration, back-up as well as zero downtime patching and recovery from failure without human intervention. It’s all done autonomously – reducing database admin tasks by 80%.
ADW tunes itself using ML algorithms, meaning that no manual performance tuning is required as workloads evolve, which typically consumes a significant amount of time for DBAs. And as opposed to the competition, self-tuning in ADW does not require any downtime.
Elastic Scaling
Oracle ADW is truly elastic. You can scale compute independently from storage and get exactly the number of CPUs you want without being constrained by fixed models. You can reduce costs by paying only for the resources you use and if your data warehouse is not being used, you can turn compute off and only pay for storage.
ADW auto-scales without any human action to up to 3x the number of base CPUs you chose to handle activity spikes, and it will scale back down when no longer needed. That means you always get high, consistent performance to empower business users across the organization with data, while reducing costs.
High Performance
Oracle ADW is not powered by generic hardware but by Exadata, Oracle’s engineered system that is the best platform to run Oracle databases.
Comprehensive Data Protection
Your data is automatically protected and the built-in Oracle Data Safe makes it easy to discover sensitive data, mask it, evaluate security risks, and implement security controls. And privileged users cannot access other users’ data with Oracle’s Database Vault technology.
Converged Database
Oracle ADW is a converged database allowing you to store data from all formats in one single database and one single source of truth. There’s no need to manage different, single-purpose databases, with different security models, high availability architectures, and management controls. You avoid data silos, and major integration challenges. Developers can also more easily handle changing business requirements over time.
Flexible Deployment
Oracle ADW is available both in Oracle Cloud Infrastructure and in the customer’s data center with Oracle Exadata Cloud@Customer.
Benefits for IT teams
- The solution is governed and secure, with robust data protection
- It is easy to provision new data marts. IT teams can rely on a simple, reliable, and repeatable approach for all data analytics requests from business departments, greatly improving productivity. They can even let business users set up data warehouse instances themselves in a self-service mode.
- Automated management means that IT teams don’t have to worry about the resources needed to manage and secure these departmental data warehouses on an ongoing basis
- They can reduce complexity and cost and spend more time on business needs, on helping to accelerate the pace of business, not having to spend time on database administration nor providing data extracts or reports
- IT teams can rely on a simple, reliable, and repeatable approach for all data analytics requests from business departments, greatly improving productivity
- IT teams don’t have to administer the solution, they can shift their time and focus from routine database administration work to innovation and higher value tasks
