Maximising performance and improving strategy using key data management trends

When harnessed effectively, this data becomes the single, most valuable asset that any organisation owns, regardless of size or sector. Companies can boost productivity and improve decision making, enabling them to stand out from the competition and offer real value to their customers.

However, the data landscape is continually changing, forcing organisations to adopt new approaches to data architecture and data management. With all businesses still battling the economic ripple effect of the global pandemic, staying ahead of the curve – and knowing which technologies and strategies to invest in - has never been more important.

Here are three of the top data management trends we are currently seeing and how businesses can utilise them to drive data strategy and future-proof, no matter what is around the corner:

1) Increased artificial intelligence and machine learning to simplify operations

It’s not necessarily surprising that artificial intelligence and machine learning are included on this list. Both technologies have become common place over the last few years as organisations utilise them to provide better insights and inform business decisions. Whether its resource allocation, supply chain management or fraud detection, AI and ML are playing an ever-increasing role.

These technologies particularly excel when it comes to creating predictive algorithms. By using stored data to predict future events, they can automatically streamline operations and improve processes in order to make a business as productive as possible. Today, many businesses are utilising them to analyse data and automate tedious, repetitive tasks. This helps to reduce workload and enable employees to focus on higher value, profitable tasks.

When incorporated into and used alongside the latest modern technologies – such as data virtualisation –  AI can enable businesses to derive true value from their historical data. It can help to simplify and enhance data discovery, enabling users to find data based on their own profiles or the profiles of their peers, recommending the use of certain data sets over others. It can also drastically improve performance throughout an entire organisation, fine tuning recommendations and self-healing any bottlenecks

2) The infiltration of consumer technologies to increase user convenience

Consumer technologies – such as voice control and Natural Language Processing (NLP) - have already established themselves as fairly common place in our personal lives. Whether it’s asking for directions, making a shopping list or even turning on the heating, all we need to do nowadays is speak a command and our virtual assistants are on hand to help.

For this technology to be utilised in a business environment, however, it needs to be able to deal with even more complicated requests, adapting to the situation and enabling business used to access key information via their phones and tablets. In business intelligence and analytics, systems are already starting to adopt NLP as a way for non-technical users to query the system. In essence, it allows users to query and access data using natural language, instead of having to know how to manipulate data through spreadsheets or understand code.

The success of this will hinge on these devices being able to access the right data at the right time. Data which will enable more seamless and even personalised user experiences.

3) The monetisation of data to stay profitable

Many companies are already seeing data as a strategic asset with real value. The valuation of some of the world’s largest companies – such as Facebook and Google – is based on how much information they can collect on individuals, whether it's their shopping habits, programmes they like to watch on television or places they like to visit.

This personal information can be sold to advertisers for profit through Application Programming Interfaces (APIs). APIs enable data from one application to interact with data from another. They already account for a significant portion of the revenue of internet giants and some business models now rely solely on selling them.

These business models often pair APIs with technologies like data virtualisation in order to make data more easily accessible. Using the virtual layer provided by data virtualisation, organisations can connect data from different sources without the need for coding. They can also incorporate security controls to show different data depending on the user or their role so businesses can ensure compliance at every level.

A data driven future

We’ve all heard the saying knowledge is power. In the business landscape, knowledge takes on the shape of data and, as such, there’s no denying that there is a lot of potential waiting to be uncovered. However, organisations need to be able to understand and utilise this data in order to drive true business value – something that has never been more important than it is today.

Regardless of industry or size, each and every business has faced challenges over the last 8 months. As the recovery efforts begin, businesses need to focus on getting ahead of the curve and investing in the technologies and data strategies that will still be both relevant and profitable in 5 years' time.