As the saying goes, you can’t manage what you don’t measure. In a data-driven organization, the best tools for measuring the performance are business intelligence (BI) and analytics engines, which require data. And that explains why data warehouses continue to play such a crucial role in business. Data warehouses often provide the source of that data, by rolling up and summarizing key information from a variety of sources.
Data warehouses, which are themselves relational databases, can be complex to set up and manage on a daily basis, so they typically require significant human involvement from database administrators (DBAs). In a large enterprise, a team of DBAs ensure that the data warehouse is extracting data from those disparate data sources, as well as accommodating new and changed data sources—and making sure the extracted data is summarized properly and stored in a structured manner that can be handled by other applications, including those BI and analytics tools.
On top of that, the DBAs are managing the data warehouse’s infrastructure, everything from server processor utilization, the efficiency of storage, security of the data, backups, and more.
However, the labor-intensive nature of data warehouses is about to change, with the advent of Oracle Autonomous Data Warehouse Cloud, announced in October 2017. The self-driving, self-repairing, self-tuning functionality of Oracle’s Data Warehouse Cloud is good for the organization—and good for the DBAs.
No Performance-Tuning Knobs
Data-driven organizations need timely, up-to-date business intelligence, which can feed instant decision-making, short-term predictions and business adjustments, and long-term strategy. If the data warehouse goes down, slows down, or lacks some information feeds, the impact can be significant. No data warehouse may mean no daily operational dashboards and reports, or inaccurate dashboards or reports.
Oracle Autonomous Data Warehouse Cloud is a powerful platform because the customer doesn’t have to worry the system itself, explains Penny Avril, vice president of Oracle Database product management.
“Customers don’t have to worry about the operational management of the underlying database—provisioning, scaling, patching, backing up, failover, all of that is fully automated,” she says. “Customers also don’t have to worry about performance. There are no performance knobs for the customer: DBAs don’t have to tweak anything themselves.”
For example, one technique used to drive Autonomous Data Warehouse’s performance is by automating the process of creating storage indexes, which Avril describes as the top challenge faced by database administrators. Those indexes allow applications to quickly extract data required to handle routine reports or ad-hoc queries.
“DBAs manually create custom indexes when they manage their own data warehouse. Now, the autonomous data warehouse transparently, and continually, generates indexes automatically based on the queries coming in,” she says. Those automatically created indexes keep the performance high, without any manual tuning or interventional required by DBAs.
- Related: Join Oracle Executive Chairman and CTO Larry Ellison and Oracle CEO Mark Hurd for the release of the world’s first autonomous database cloud service. Register now.
The organization also can benefit from the automatic scaling features of Autonomous Data Warehouse. When the business requires more horsepower in the data warehouse to maintain performance during times of high utilization, the customer can add more processing power by adding more CPUs to the cloud service, for which there is an additional cost. However, Avril says, “Customers can scale back down again when the peak demand is over”—eliminating that extra cost until the next time the CPUs are needed.
Customers can even turn off the processing entirely if needed. “When a customer suspends the service, they pay for storage, but not CPU,” she says. “That’s great for developers and test beds. It’s great for ad-hoc analytics for people running queries. When you don’t need a particular data warehouse, you can just suspend it.”
Freedom for the Database Administrator
Performance optimization, self-repairing, self-securing, scalability up and down—those benefits serve the organization. What about the poor DBA? Is he or she out of work? Not at all, says Avril, laughing at the question. “They can finally tackle the task backlog,” adding more value to the business, she says.
Avril explains that DBAs do two types of day-to-day work. “There are generic tasks, common to all databases, including data warehouses. And there are tasks that are specific to the business. With Oracle’s Autonomous Data Warehouse, the generic tasks go away. Configuring, tuning, provisioning, backup, optimization—gone.”
That leaves the good stuff, she explains: “If they aren’t overloaded with generic tasks, DBAs can do business-specific tasks, like data modeling, integrating new data sources, application tuning, and end-to-end service level management.”
For example, DBAs will have to manage how applications connect to the data warehouse—and what happens if things go wrong. “If the database survives a failure through failover, does the application know to failover instantly and transparently? The DBA still needs to manage that,” Avril says.
In addition, data security still must be managed. “Oracle will take care of patching the data warehouse itself, but Oracle doesn’t see the customer’s data,” she says, “DBAs still need to understand where the data lives, what the data represents, and which people and applications should get to see which data.”
No need for a resume writer: DBAs will still have plenty of work to do.
For C-level executives, Autonomous Data Warehouse can improve the value of the data warehouse—and the responsiveness of business intelligence and other important applications—by improving availability and performance. “The value of the business is driven by data, and by the usage of the data,” says Avril. “For many companies, the data is the only real capital they have. Oracle is making it easier for the C-level to manage and use that data. That should help the bottom line.”
For the DBA, Autonomous Data Warehouse means the end of generic tasks that, on their own, don’t add significant value to the business. Stop worrying about uptime. Forget about disk-drive failures. Move beyond performance tuning. DBAs, you have a business to optimize.
Alan Zeichick is principal analyst at Camden Associates, a tech consultancy in Phoenix, Arizona, specializing in software development, enterprise networking, and cybersecurity. Follow him @zeichick.
