The role autonomous technologies play in successful business transformation

Why is the autonomous database a game changer and how can it help transformation initiatives succeed?

As we saw in the previous article, having an autonomous database offers a wide range of benefits to any organisation. One key benefit is in liberating the database administrators from mundane tasks such as the management and maintenance of the database. In leveraging automation and AI to handle the bulk of the maintenance, organisations free up the database administrators to focus their energies on data analytics and business insight, and in doing so, they deliver greater competitive advantage back to the organisation.

Another reason that the autonomous database is of such great value to organisations is because it can facilitate one of the most challenging, but necessary, strategic exercises in modern enterprise: business transformation.

Business transformation has been listed as the top CIO concern across almost all industries, according to Gartner research. A recent study showed that 11 of 15 industries surveyed ranked transformation as a top three business priority. Furthermore, nearly a half – 47 per cent – of CEOs are being challenged by their boards to make meaningful progress in transformation.[1]

Businesses undertake transformation projects for a wide range of reasons, but most significantly, a transformation project is done in the interests of the business first, with technology gains a secondary concern. It's a strategic initiative to gain competitive advantage, in other words. Across all lines of business, transformation promises greater efficiency, security, an improved customer experience, more complex use of data, greater insight, and improved collaboration within the organisation.

Unfortunately, less than 30 per cent of transformation projects succeed[2], and one of the reasons that failure is so frequent is that the organisation chooses the wrong platforms and technologies for the transformation rollout.

The database's role in transformation

Ovum research shows that only 12.2 per cent of enterprises across Oceania, Eastern and South-Eastern Asia have AI-based data mining/search fully in production. This lifts to 25.4 per cent of enterprises in Central and Southern Asia, but across the entirety of the region these low numbers are despite interest in AI-based mining/search being incredibly high.[3]

AI is an important tool for achieving transformation, as it can be leveraged to generate deep data analytics and drive actionable insight rapidly. With speed and the integration of complex data being a core performance indicator - that executives use to measure the success of a transformation exercise - Ovum notes that the Oracle autonomous database can become a central platform and a real game changer for the organisation's efforts in rolling out AI.

"Although adoption of autonomous databases remains at a relatively early stage, AI and machine learning features are strong drivers for enterprise migration to cloud-based database environments," the Ovum report notes.

Migration to the cloud is an important step in transformation, as the cloud offers a technology solution that can cope with the post-transformed environment. Cloud-based platforms help to cut runtime costs, give organisations an enhanced (and rapidly scalable) opportunity to run mission-critical workloads in truly secure environments, and offer self-repairing processes to address faults.

Ovum defines three capabilities within the autonomous database that define it as a platform for automation and, from there, bring the capabilities of machine learning, AI, and analytics into the organisation:

  • Self-driving: It reduces human labour via auto-provisioning, security, monitoring, tuning, upgrading, backup, and recovery.
  • Self-secure: It understands access patterns and protects them from internal and external threats by applying security patches automatically, and with no downtime.
  • Self-repairing: It offers up to 99.995% availability, with fewer than 2.5 minutes planned and unplanned downtime per month.

"As Oracle's ADWC clients are beginning to discover, the future is about analysing data, not how data is administered," Ovum notes.

This echoes Gartner's perspective on business transformation. "Some organisations see digital business as an opportunity to totally reinvent themselves and their business models" Gartner notes. "Other enterprises and their functions are looking to leverage technology to optimise and augment existing operations."[4]

Certainly, bringing AI and machine learning into the organisation is a way of complementing the work that the database administrators do (and freeing the administrator's time up to take on a data scientist or data analyst role within the organisation). This then allows the organisation to achieve its greatest priorities for transformation projects around efficiency, productivity, and competitive advantage.

In other words, through the adoption of the Oracle autonomous database, organisations can ensure that they navigate one of the most complex IT challenges, introducing real cloud based AI technology to help achieve their transformation goals.

Want to get hands on with Oracle autonomous database, register to attend an Oracle Cloud Insight Community Meetup in your city.

Find out more about the Oracle autonomous database here.


[1] https://www.gartner.com/smarterwithgartner/is-digital-a-priority-for-your-industry/

[2] https://www.mckinsey.com/business-functions/organization/our-insights/unlocking-success-in-digital-transformations

[3] Oracle's AI-based, self-driving database gains traction in Asia

[4] https://hbr.org/sponsored/2018/11/every-organizational-function-needs-to-work-on-digital-transformation