Five data analytics predictions and trends for 2022

The accelerated wave of remote working and digitisation has become essential for more businesses than ever before. Here are our top five predictions from Kerry Koutsikos, regional vice president, MEA, at Alteryx that will drive business transformation in 2022 and beyond.

Democratisation of data will be a business game-changer          

Data, after it is transformed into useful insight through analytics, continues to increase in value. With the right strategy, that value can exist in perpetuity. In 2022, we will see the rise of data trusts and new frameworks as organisations shift their mindsets to sharing, rather than hoarding, data. 

Businesses will move from being data-hoarders to driving real insights and democratising analytics. The arrival of cheap cloud storage, AI driven auto-insights, and the ever-expanding digital exhaust has caused organisations to simply capture and store as much data as possible without doing much with it.

Adopting solutions that speed the time to meaningful business insight from their analytic platforms will be critical in the new year, allowing enterprises to drive business forward with data-driven intelligence.

We will also see the increasing use of synthetic data – any data not sourced through direct measurement – as well as differential privacy and other techniques to ensure security, privacy, and legit use of data.

Upskilling and great resignation

Digital Transformation 2.0 will usher in a culture of analytics across business units as more large organisations provide the self-service technologies and training to ensure the average knowledge worker is both set up for success and able to directly perform analytics.

Businesses will need to fast-track employee upskilling programs to gain competitive insights and value from their data if they want to keep pace with their market. A recent Alteryx survey in the UAE and Saudi Arabia found that the majority of workers believe more training in data work would result in better (75 percent) and faster (69 percent) decisions.

Next year will also be the year of the chief transformation officer. We’ll see a title and focus shift from chief data officer, to chief analytic officer, to chief transformation officer as the role of those leading the digital transformation journey focuses more on results instead of the data or analytic methods used. As a positive side effect of the “great resignation,” tools with an established userbase or high net promoter score (NPS) will thrive.

With the continuing democratisation of analytics, data scientists now need to evolve from problem solvers to teachers. Organisations are now looking to fill these roles with someone who can both articulate and explain – not just to code, but also to encourage people to be creative and think critically. However, there is an existing skills gap between data scientists and those they need to teach. This gap will need to be bridged to maximise the potential of individual data strategies in 2022.

Artificial Intelligence (AI) /Machine Learning (ML) become more intelligent

Fragmentation in the data and analytics space will level-off. In recent years, the AI/ML space has been complex, with far more companies entering the space than the year prior. However, we will begin to see this trend curve and plateau as we enter a more mature space with increased consolidation in 2022.

More companies will invest in AI-driven automated insights to complement their existing dashboards. No-code and low-code will simplify and democratise AI. While data scientists will continue to focus on high-value problems, the number of people who are able to participate in advanced analytics utilising automation, computer vision, natural language processing, and machine learning will increase.

More responsible AI will bridge the gap from design to innovation. While companies are beginning to think about and discuss AI ethics, their actions are nascent. Within the next year we will see an event that will force companies to be more serious about AI ethics – integrating transparent explainability, governance, and trustworthiness at the center.  

Analytics automation and employees will forge a union

The reliance on process automation is increasing alongside the exponential growth of the data held by organisations. With the speed at which business happens, people need insights that answer key questions faster to drive process improvement. The ability to automate has greatly impacted the speed to insight, and business leaders are no longer satisfied waiting days or weeks for answers they know they need in minutes or hours.

People and analytics will forge a union, but analytic automation is not about replacing the human – it’s about identifying processes that can be automated so analytics professionals can focus on the next big question to drive business forward. The best analytic outcomes are driven by the people closest to the question – people with vital context which cannot be replicated by technology. The power of humans is amplified with the automation of the mundane, which enables people to focus on the higher value opportunities.

In the new year, analytic software will become more specialised to address specific use cases for different verticals and functions. This customised approach will enable businesses to focus on getting better insights from their software and align those insights with business outcomes.  

Businesses will reach for the clouds

The migration in the cloud will necessitate closer relationships between business users and IT teams.

While the shift to the cloud offers numerous opportunities and benefits for organisations, such as scaling analytic processes, it also means they are subject to governance around data control, data ownership and data access. The reality is many businesses still struggle to mitigate shadow IT – users downloading a tool and running it locally on their desktop. This denies others the opportunity to utilise, learn from, and replicate their analytic processes.

For organisations to mature and operate in secure and governed cloud environments, this attitude needs to change. This starts with the business user and IT engaging more to answer the questions: “Where’s all this data going? What’s being done with it?” and to jointly agree upon a solution that empowers the business users. 

Next year, analytics will finally cross the chasm into the cloud. Cloud adoption is steadily growing as businesses seek to leverage the big data already in cloud repositories. These organisations are primed to take advantage of cloud native computing and reap the benefits of easier analytics access.