Theme 1: Democratization of Data                    

Alan Jacobson, Chief Data & Analytics Officer at Alteryx

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

David Sweenor, Senior Director of Product Marketing, Alteryx

1. Data is not the new oil; data is a renewable energy source. Data, after it is transformed into useful insight through analytics, continues to increase in value and that value will exist in perpetuity – the more that is extracted from it, as opposed to oil, which is burned and then gone.
2. We will see the rise of data trusts and frameworks evolve and organizations will shift their mindsets to sharing rather than data hording. We’ll see increasing use of synthetic data, differential privacy, other techniques to ensure security, privacy and legit use of data.
3. The digital world needs to ditch paper. Many organizations are still working from printed documents leaving pertinent data on the table that needs to be extracted. Getting the data out of paper has been difficult to date, but with computer vision and text analytics capabilities, organizations can extract insights from shipping invoices, paper records, receipts, etc. 

Jay Henderson – VP Product Management – Alteryx

1. Businesses will move from being data-hoarders to driving real insights and democratizing analytics. Right now, organizations are drowning in data but still thirsty for insights. The arrival of cheap cloud storage and the ever-expanding digital exhaust has caused organizations 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 allow enterprises to drive business forward with data-driven intelligence. The emergence of AI driven auto-insights capabilities are a key enabler of this change.

Theme 2: Upskilling / Skills / Great Resignation

Libby Duane Adams, Chief Advocacy Officer at Alteryx

1. Businesses are forced to fast-track employee upskilling programs. While many businesses are talking about ways to upskill their employees and equip them with the tools, they need to deliver analytics for business impact, a recent Alteryx survey found that the majority of workers believe more training in data work would result in better (75%) and faster (69%) decisions. As businesses seek to gain competitive insights and value from their data, they will need to quickly address upskilling needs if they want to keep pace with the market.
2. Universities must replace spreadsheets and pivot tables with modern data analytics tools to educate the next generation of knowledge workers now. Graduates need to show that they can work with data from the prep and blend stages all the way to analyzing the insights to raise their resumes to the top of a recruiters’ search. Educational institutions need to adapt to maintain positive job placement rates.

Alan Jacobson, Chief Data & Analytics Officer at Alteryx

1. 2022 will 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 the results than the data or the analytic methods used.
2. As a positive side effect of the “great resignation,” tools with an established fanbase or high Net Promoter Scores will thrive. As the people move from company to company, we will see beloved technologies travel with them and become an established part of their new stack.
3. With the continued democratization of analytics, data scientists need to evolve from ‘problem solvers’ to ‘teachers.’ Organizations are now looking to fill these roles with someone who can articulate and explain – not just code to encourage people to be creative and think critically. However, there is an existing skills gap between data scientists as practitioners and those as teacher.

David Sweenor, Senior Director of Product Marketing, Alteryx

1. The role of the ‘citizen data scientist’ will evolve. Organizations will focus more on the relationship between people and AI, leading to increased spend on upskilling people as data literacy evolves into AI literacy. We will move away from the term “citizen data scientist” and towards “AI or analytics literate.” Businesses will become more dependent on collective intelligence, the idea that better business decisions can be made by machines and humans working together. 

Jay Henderson – VP Product Management – Alteryx

1. Data scientists will no longer be the only workers that understand analytics. As we continue to democratize analytics and empower teams with the skills needed to understand data, organizations will no longer need to rely solely on a data scientist to make sense, and gain insights, from data. Empowering a much larger group to create insights and allowing the data scientists to focus on the problems where they can have the most impact.

Theme 3: Artificial Intelligence/Machine Learning

Alan Jacobson, Chief Data & Analytics Officer at Alteryx

1. Fragmentation in the data and analytics space will level-off. In recent years, the AI/ML space has been complex, with 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.

David Sweenor, Senior Director of Product Marketing, Alteryx

1. More responsible AI will bridge the gap from design to innovation. While companies are starting to think about and discuss AI ethics, their actions are nascent, but within the next year we will see an event that will force companies to be more serious about AI ethics. An increasing number of companies will get more serious about AI ethics with transparent explain ability, governance and trustworthiness at the center.  
2. AI becomes demystified and more approachable for the everyday business user. No-code and low-code will simplify and democratize AI – although data scientists will continue to focus on high value problems, the number of people who are able to participate in advanced analytics utilizing automation, computer vision, natural language processing, and machine learning will increase.   More companies will invest in AI-driven automated insights to complement their existing dashboards.

Theme 4: Analytics Automation

Libby Duane Adams, Chief Advocacy Officer at Alteryx

1. The reliance on process automation is increasing with exponential growth of business data. 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 to receive in minutes or hours.
2. People and analytics will forge a union. Analytic automation is not replacing the human, it’s identifying processes that can be automated so analytics professionals can focus on the next ‘big’ question pertinent to driving business forward. The best analytic outcomes are driven by the people closest to the business questions with the context which will not be replace the human. The power of humans is amplified with the automation of the mundane which enables the human to focus on the high value opportunities.

Jay Henderson – VP Product Management – Alteryx

1. Generic analytic software produces generic results – to drive business outcomes through analytics vendors will shift towards vertical and functional solutions. Analytics vendors will take a customized approach for users within different verticals like financial services, CPG and retail, as well as for different business functions like finance, marketing and sales. In the next year, analytic software will become more specialized to address specific use cases for different verticals and functions. This customized approach will enable businesses to focus on getting better insights from their software and align those insights with business outcomes.  

Theme 5 – Cloud

Jay Henderson – VP Product Management – Alteryx

1. The migration in the cloud will necessitate the conversations for the business user and IT to become besties. While the shift to the cloud offers numerous opportunities and benefits for organizations, like scaling analytic processes, it also means they are subject to governance around data control, data ownership and data access. The reality is a lot of what many organizations are guilty of is shadow IT – users download a tool and run it on a desktop under the assumption they don’t need permission. For organizations 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 answering the questions, ‘Where’s all this data going? What’s being done with it?’ and to jointly agree upon a solution that IT approves of and has governance over, while still empowering the business users. 
2. Next year, analytics finally crosses the chasm into the cloud. Cloud adoption is steadily growing as businesses seek to leverage big data already in cloud repositories, take advantage of cloud native compute, and provide easier access to analytics.