Data analytics Forecasts - Trends for 2022 - Digitilization - New technology - Techxmedia

Five data analytics forecasts and trends for 2022

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By Kerry Koutsikos, Regional Vice President, MEA, at Alteryx 

Many firms advanced toward digitization in 2021, necessitating the use of new technology and data-driven analytics to make educated decisions.

Remote working and digitization have become more important than ever before for a growing number of enterprises. Here are Kerry Koutsikos’ top five forecasts for business transformation in 2022 and beyond, as provided by Alteryx’s Regional Vice President, MEA.

Trend 1: Democratization of Data will be a business game-changer

The value of data increases as it is translated into usable insight through analytics. That value can last indefinitely with the appropriate method. As corporations alter their mindsets to sharing rather than hoarding data, we will see the growth of data trusts and new frameworks in 2022.

Businesses will transition from data hoarders to real-time insight generators and analytics democratizes. With the introduction of low-cost cloud storage, AI-driven auto-insights, and the ever-increasing digital exhaust, enterprises have been compelled to simply acquire and store as much data as possible without doing much with it. In the coming year, organizations will need to adopt solutions that allow them to get significant business information faster from their analytic platforms, allowing them to move forward with data-driven intelligence.

We’ll also see more synthetic data – data that isn’t derived from direct measurement – as well as differential privacy and other approaches to protect data security, privacy, and legal use.

Trend 2: Upskilling and Great Resignation

As more major firms give self-service technology and training, Digital Transformation 2.0 will usher in a culture of analytics across business units, ensuring that the average knowledge worker is both set up for success and able to directly execute analytics.

If companies want to stay ahead of the competition, they’ll have to speed up personnel upskilling initiatives in order to acquire competitive insights and value from their data.

According to a recent Alteryx poll conducted in the UAE and Saudi Arabia, the majority of workers believe that additional data work training will result in better (75%) and faster (69%) decisions.

In addition, the year 2022 will be the year of the Chief Transformation Officer. As the job of individuals leading the digital transformation journey focuses more on results rather than the data or analytic methodologies used, we’ll see a title and focus move from Chief Data Officer to Chief Analytic Officer to Chief Transformation Officer. Tools with a large user base or a high Net Promoter Score (NPS) will thrive as a result of the “great resignation.”

With the democratisation of analytics continuing, data scientists must now transition from problem solvers to teachers. Organizations are increasingly searching for employees who can express and explain – not only how to code, but also how to encourage others to be creative and critical thinkers. There is, however, a skills gap between data scientists and those who must train them. To realise the potential of individual data strategies in 2022, this gap must be closed.

Trend 3: Artificial Intelligence (AI) /Machine Learning (ML) becomes more intelligent 

The data and analytics space will become less fragmented. The AI/ML space has become increasingly sophisticated in recent years, with many more startups joining the space than the year before. However, when we enter a more mature industry with greater consolidation in 2022, this trend curve will begin to flatten and plateau.

To supplement their existing dashboards, more firms will invest in AI-driven automated insights. No-code and low-code AI will make AI more accessible. While data scientists will continue to focus on high-value challenges, more people will be able to participate in advanced analytics involving automation, computer vision, natural language processing, and machine learning.

AI that is more responsible will help to bridge the gap between design and innovation. While businesses are beginning to consider and discuss AI ethics, their activities are still in the early stages. We will witness an event within the next year that will drive firms to take AI ethics more seriously, putting transparent explainability, governance, and trustworthiness at the forefront.

Trend 4: Analytics Automation and employees will forge a union 

The use of process automation is growing in tandem with the exponential expansion of data possessed by businesses. People need insights that answer important questions faster to promote process improvement in today’s fast-paced business environment. The capacity to automate has had a significant impact on the speed with which corporate executives can gain insight, and they are no longer content to wait days or weeks for answers they know they need in minutes or hours.

People and analytics will become one, but analytic automation is about finding activities that can be automated so that analytics specialists can focus on the next big question to push business forward. The best analytic solutions are driven by those who are closest to the subject – humans who have critical context that technology cannot duplicate. The power of humans is enhanced by the automation of routine tasks, allowing people to concentrate on higher-value opportunities.

Analytic software will grow more specialised in the coming year to handle unique use cases for various verticals and functions. Businesses will be able to focus on generating greater insights from their software and aligning those insights with business goals thanks to this personalised strategy.

Trend 5 – Businesses will reach for the clouds 

Closer collaboration between business users and IT teams will be required as a result of the cloud migration.

While moving to the cloud provides organisations with several opportunities and benefits, such as growing analytic operations, it also means they are susceptible to data control, data ownership, and data access governance. Many firms are still struggling to combat shadow IT, which occurs when users download a programme and execute it locally on their desktop. This prevents others from using, learning from, and replicating their analytic procedures.

This attitude must alter if firms are to mature and operate in secure and managed cloud environments. This begins with a greater level of engagement between the business user and IT in order to address the questions: “Where is all this data going?” “What are you going to do with it?” and to come to an agreement on a solution that will empower business users.

Analytics will finally bridge the abyss into the cloud next year. As businesses attempt to use the vast data already in cloud repositories, cloud usage is constantly increasing. These businesses are well positioned to profit from cloud native computing and have quicker access to analytics. 

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