AIOps in the spotlight - Part 2

By Richard Smith, SVP Technology at Oracle.

We have entered a truly data-driven world. According to Domo’s Data Never Sleeps 6.0 report, there are 473,400 tweets made, 49,380 photos posted on Instagram, and almost 13 million text messages sent every minute of every day. Data like this holds immense value for those able to collect, organise and leverage it.

For businesses today, data is the new battleground, and being able to master it through sound management has a direct impact on an organisation’s success. This makes the lowly database, whether on-premise or in the cloud, the beating heart of the enterprise. If left unoptimised and running slowly, employee productivity and customer experience will suffer, and the data within cannot be leveraged for innovation. Furthermore, if the database is not secure, the company faces a greater risk from security breaches.

Data management is clearly integral to the successful running of an organisation, but the task only gets harder as databases grow in size and complexity. Enterprises must look to new solutions driven by automation and machine learning to unlock their data potential.

To err is human

Traditionally, the task of data management has fallen to the database administrator (DBA). Their role is to create, modify and tune enterprise databases for maximum performance and security. It’s a role that is far more complex than it perhaps initially appears, and it should not be underestimated in terms of importance.

When an employee or client wants to retrieve data, the process is complex and can consume a great deal of time, as well as compute and disk-access resources. This is especially true at peak times when thousands or potentially millions of hosts are trying to access the database. 

This manual approach is beginning to crumble under the weight of organisational data. Traditional database management has become extremely time-consuming and expensive: 72 per cent of IT budgets are spent simply maintaining existing information systems. Time and resources could be better spent elsewhere, such as on IT innovation.  

With DBAs often finding themselves managing 50 or more databases a day, human error can often result – such as failing to apply a security update or being unable to keep a database fully optimised.

These errors can be disastrous for uptime and security, but there’s a more fundamental problem. A company unable to keep its databases performant is less able to utilise its data effectively. Employees will struggle to get the data they need and will be slower to make decisions, while customers will suffer from an unsatisfying user experience. Every second of every day the company is running slower than the competition and, gradually but surely, falling behind the pace of the market.

The benefits of the autonomous approach

To remain relevant and competitive in the long run, companies must explore new ways to reduce the effort needed to maintain databases, limit downtime and, above all, accelerate performance and as a result innovation.

While putting databases in the cloud has already gone some way towards taking human effort and responsibility out of active database management, a revolution is taking place behind the scenes.  Increasingly, with the advent of emerging technologies like artificial intelligence, machine learning and automation, autonomous systems are being born.

The resulting ‘autonomous database’ is self-driving, self-securing and self-repairing, making it both easy and cost effective to adopt, while freeing IT up to focus on innovation and value-adding tasks.

A data shot to the arm

Above all else, an autonomous database gives organisations a data shot to the arm - the ability to better access and utilise their data faster and more efficiently, enabling greater productivity and a more seamless, competitive customer experience.

Oscar Jalón, IT director, Santiveri, a leading producer of organic food, beverages and beauty products in Spain, has experienced exactly this. “To stay ahead of the rising competition in the organic food and beverage market, we need a granular understanding of our business, but our existing IT systems were struggling to keep up.  With Oracle Autonomous Database, we can execute queries 75 to 80% faster.  This means we can see, not only which products are selling well, but exactly where the sales are happening, right down to the individual store and time of day, and then work out the optimum extra resources to put behind a push. The sooner you can make that happen, the sooner you sell more,” said Jalón. “We are now applying this speed and smarter decision-making right across the business, to areas like R&D and customer service, and can do so with less resources. As the technology is self-securing and repairing it is giving our people the freedom to focus on innovation and business improvement.”

The direction of travel is clear – databases are only going to get larger, more complex and more important to business success. The companies that will be successful are those that fully utilise the benefits of the cloud and other emerging technologies arriving on the scene, while marring their human talent with the self-learning capabilities of the machines. The resulting data injection will enable these companies to become truly data-driven, able to boost areas critical for success and drive the customer and employee experience to new heights.

Tim Flower, Global Director of Business Transformation at Nexthink, warns that IT services in the enterprise are now interconnected to such an extent that isolated failure can start a chain reaction causing customer frustration, employee dissatisfaction and revenue shrinkage:

To address this challenge, more strategically-minded CIOs and their IT departments are electing to use advanced analytics and artificial intelligence (AI). The technology helps to comprehensively monitor and assess the user experience of devices and applications across the organisation in real-time. Leveraging the power of intuitive algorithms, companies can take a more advanced approach to IT in the enterprise, by using end-user performance data to identify IT-related issues automatically and generate IT tickets. Additionally, AI-based tools can remediate minor issues as they pop up without any human intervention — freeing up IT staff to tend to the most pressing concerns – or better yet, more strategic and value-add assignments.

For example, service desk and IT operations staff can solve problems quicker than it takes users to realise the issue and contact support, with alerts and recommended actions about endpoint and user experience issues coupled with the ability to automatically resolve them in one click. Meanwhile, staff wins the support of end users when they empower them with the ability to quickly resolve their own issues or even fully automate the remediation process so neither the employees nor IT resources are impacted to get back to their desired state.

AI and machine learning (ML) algorithms can sift through reams of data and identify issues faster than a human ever could, which is why successful organisations are choosing to add AI into the mix to bolster the abilities of their IT staff to tackle tech problems and take the end-user out of the process. By letting the algorithms do what they're best at, businesses can reduce the overall number of IT support tickets, eliminate employee frustration related to IT disruptions and most importantly, ensure employees across every department have devices and applications consistently available so they can do their jobs properly.

This integrated approach to digital experience management, which combines real-time endpoint monitoring and analytics with both end-user engagement and automatic remediation of incidents, even before they occur, can truly revolutionise the role of IT managers. And employees have a job to do; notifying IT about issues shouldn't be bolted on to that.’