Features Hub

AI and machine learning are set to transform data management

Thu 20 Jun 2019 | Krishna Subramanian

AI-based data management thinks outside the box, offering more intelligent ways to manage business needs

For many companies, the success of companies such as Airbnb, Netflix and Uber makes the attraction of “disruptive technology” seem very appealing. But when it boils down to it – what exactly is disruptive technology, and just how disruptive should it be?

Although these types of businesses are effective at deploying technology that will disrupt settled markets, that doesn’t mean that the technology in itself is disruptive. Businesses that have well-established architectures and IT infrastructures do not have the agility and flexibility that newer companies, such as Netflix, have when deploying new technology. Nevertheless, these more traditional organisations can still adapt. If anything, the success of startup businesses like Airbnb and Uber strengthen the message that for organisations to remain competitive, they need to adapt and transform to new architectures, and swiftly. However, this needs to be balanced with the cost of business disruption.

Business disruption can be detrimental to an organisation, so it’s important that the technology is transformational without wreaking havoc. Disruptive technology cannot be adopted exclusively for its own sake, or because an organisation believes it can reinvent itself and become a Netflix overnight – it can’t. The best disruptive technology to adopt its transformational, but not destructive. It enables a business to transform to a newer, simpler and better way of doing things, without requiring the company to disrupt users and take a hit on productivity, service and sales.

There are technologies that enable businesses to create new and more efficient ways of working – but without interrupting the overall business. An example of this is Amazon, Apple, Facebook and Google – all are testament to the power of successfully innovating, without intrusive IT projects.

Transformation starts at the data management level

The data management level is the best place to begin when organisations look towards striking a practical balance. Data is the lifeblood of most companies, and being able to transform the ways in which this information is collected, stored and managed, will allow the business to innovate.

“AI-based data management thinks outside the box, offering more intelligent ways to manage business needs”

Many organisations struggle with storage costs, the vast volume of data that is generated, and data silos. Using technology to transform the approach to data management and overcome these obstacles will leave businesses in a far better position to successfully evolve. Two technologies that have the capability to deliver massive disruptive change in this area, and across the whole organisation, are AI and machine learning.

AI and machine learning are disruptive enablers as they transform technology that is essentially low-level automation into intelligent, learning systems. Higher levels of automation means simplicity and efficiency. AI’s dependence on data will lead to substantial transformation in the data management industry. Adaptive automation and machine learning will enable data management software to perform in smarter ways, by both observing and leveraging patterns. AI-based data management thinks outside the box, offering more intelligent ways to manage business needs.

AI will also allow organisations to use intelligent software to move away from cumbersome, monotonous, error-prone and time-consuming rule-based policies to setting goal-based policies. Rule-based data management policies typically rely on a human to predict every single eventuality and program a rule for it. Moving to goal-based policies, where intelligent software works out the appropriate way to achieve them, will ensure IT is in control of the outcome without the manual heavy-lifting and errors associated with the rule-based approach.

Organisations can also benefit from the improved search and discovery that AI delivers. A significant roadblock to adoption of big data has been the difficulty in finding the right data sets to analyse, with data strewn across billions of files and different storage silos, both on premises and in the cloud. AI can drive efficient search and discovery of data to help extract value from it more efficiently, even at today’s massive scale of data. With AI, intelligent software can pull information from a much wider data lake, no matter where it is stored.

While not every company can be an Airbnb or Uber, every business can be transformed. Perhaps the time has come to evolve the way we see disruption. Disruptive technology, when applied through transformation can help to elevate organisations. The transformative effects of AI and ML in data management will aid businesses on their quest to becoming more adaptable, agile and efficient. Data drives business decisions, and being able to leverage the benefits of an innovative data management platform will mean organisations will have the competitive edge.

Experts featured:

Krishna Subramanian



AI artificial intelligence data management machine learning
Send us a correction Send us a news tip