The past few years have seen increased digitisation across multiple industries as more and more businesses shift from traditional techniques for example on-premise systems to modern data analytics tools. We have already seen data continue to be the driving force in 2022, something that has continued since the pandemic.
We have identified 5 trends that will impact your business in the new data-driven world of 2022.
Data governance will continue to rapidly grow as the data market grows dramatically with the market expected to grow by over 5.2 billion dollars by 2026. We are noticing a growing trend in DataHub and OpenLineage which is seeing businesses move to open-source solutions in that field from giant and expensive ones (from Informatica, IBM, SAP and others).
As open-source solutions become increasingly mature and more relatively small companies start possessing huge amounts of data there is a demand for such kinds of solutions, but they still have difficulty spending a lot of money on them.
A massive topic is also centred around organisational changes such as implementing data mesh architectures and the amount of challenges that it brings to data governance.
There is a growing trend in data democratization, which is the ability for information in a digital format to be accessible to the average end-user. The goal is to allow non-specialists to be able to gather and analyse data without requiring ‘outside help’. We will also see an increasing demand for the role of Chief Data Officer etc. This isn’t a new field topic, but it seems there will be more and more talks about it in the coming years.
Artificial Intelligence will play a leading role in influencing operational efficiency and business decision-making in 2022 with a recent survey estimating the worldwide AI software market will reach $62 billion in 2022. AI has grown beyond the hype with around 57% stating they use at least one AI operation. AI has increasingly gotten better, and algorithms are growing faster than ever and become more accessible. Many organisations are still at the beginning of their AI journey, so it is the perfect opportunity to get their automated strategy right from the beginning, building from the ground up and bringing everyone together ‘in one tent’.
AI could also help plug the gap with the skills shortage by looking for alternative ways to automate and extract data from their services when resources are tight. Businesses that use AI tools will enable them to analyse data and quickly build ML models in their services.
We will even start to see businesses utilising AI in data governance initiatives such as labelling data and even producing narratives from data. These solutions are still quite “raw” but are trending in demand.
The year of the cloud
With a recent survey indicating that end-user spending on public cloud services will grow 21.7% and reach $482 billion, 2022 is the year of the cloud. In another report, 70% of companies said they will use hybrid-cloud or multi-cloud platforms as part of a distributed IT infrastructure in 2022. Cloud infrastructure is the key to scale and lets people deploy applications when needed and globally. The cloud also gives the opportunity to scale, being able to pivot at pace without ‘breaking the bank’.
Hybrid-cloud is not about compromising between approaches, it’s about combining strengths from different cloud providers. Essentially, data that needs to be accessed quickly can be kept on private servers and more sensitive data can be kept private – giving businesses the best of both worlds. Multi-cloud environments allow a business to use multiple cloud services from different suppliers. Businesses are shifting to multi-cloud to increase efficiency, reduce costs from on-promise and improve performance.
As the Internet of things is becoming more common, we must consider how often do we think about data ethics. It is too easy to do harm with data and as it becomes more common, businesses have a moral duty to make sure the data used is ethical. As the volume of data grows, it is more important than ever for businesses to deliver transparency, and trust to reduce the technology’s potential for harming people, including bias and discriminatory lending. UK regulators have warned lenders on the use of AI on loan applications to ensure ML does not discriminate.
It relies on the public and private sectors to work together when lines are crossed and to constantly look at whether ethical standards stay at the same pace as new data. It needs to be questioned; how can we eliminate data harm? The actions of businesses matter where they use data responsibly.