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InRule 2022 Predictions: High-quality data priorities and business application modernization in the year ahead

vmblog predictions 2022 

Industry executives and experts share their predictions for 2022.  Read them in this 14th annual VMblog.com series exclusive.

High-quality data priorities and business application modernization in the year ahead

By Alan Young, CPO at InRule Technology

Just about everything we do in our lives today generates data, creating a data deluge that holds tremendous potential for the enterprise. This abundance of data is valuable for automation technologies, including artificial intelligence (AI) and machine learning (ML), that improve based on data supply. However, one of the most significant issues that the enterprise actively faces is data quality and management. For example, when ML models and applications are powered by low quality data it can produce subpar and inaccurate results.

To experience the full power of automation technologies, high-quality, timely data is required to make accurate decisions and predictions - especially in mission-critical scenarios. Identifying and funneling high-quality and uniform data into business applications and technologies will be a key differentiator for companies to win, serve and retain customers in the coming year.

Below are four predictions I see coming to fruition in 2022:

To combat data issues, we will see a rise in data fabric technologies and practices.

Data fabric will become a vital technology and practice because it accelerates big data use cases. It does this by automating the process of collecting, normalizing, and aggregating data from numerous disparate sources in real-time, and delivers comprehensive and trustworthy operational data. The data can then be used for various business applications. With data fabric technologies and practices, companies can improve operations, enhance customer experience, and maximize business outcomes.

We'll continue to see more automation across the enterprise, impacting both business and the workforce.

Software providers will blend their offerings, and we'll see solutions increasingly combine decision automation, process automation, RPA, AI, ML and related technologies, to increase value creation and transparency. This will empower companies to take on more complex use cases and achieve greater business growth. As more processes are automated, employees will need to perform fewer repetitive, low-value tasks. However, there will still be plenty of issues and use cases that will need human cognition and intervention. Employees will be required to handle these tasks that require more intelligent thinking and act as guardrails to these automations.

As we boost automation, data quality, orchestration and accessibility management will become more critical requirements.

Algorithms and automation rely on data, and the effectiveness and quality of these algorithms and automation is directly proportional to the quality and applicability of the data used. Organizations will need to collect, standardize, aggregate, and distribute data to applications more efficiently and, very likely, always in a just-in-time model assuring data currency. Therefore, concepts such as data fabric will become even more critical in 2022 and beyond. Likewise, standardized practices for governance of this expanded data landscape will also continue to be important.

Antiquated systems will struggle to compete

Digital transformation is still the one of the most important enterprise activities when it comes to business competitiveness in the digital age. Organizations need to update and modernize their legacy systems to compete in today's markets and comply with ever-changing regulations. For example, low-code platforms that allow organizations to build applications and automate decisions, processes and more will be crucial. Going further, these applications need to improve on two key fronts. First, they need to get better at capturing, configuring, processing and maintaining data. Second, they need to incorporate the use of AI/ML to make and explain predictions that enhance their applications. In doing so, organizations will be able to leverage the power of a comprehensive low-code strategy.

The quality and management of data presents a complex challenge that many organizations are still determining how to address. While some companies are focused on building robots to mimic human tasks or other fancy but low-impact use cases of AI, I would argue that the most important focus for 2022 is feeding technology high-quality data to automate and enable more complex decisions.

This isn't to say that we should view automation technology as a replacement for our colleagues, as some would say; we have different strengths for a reason. However, improving data quality and working with platforms that allow citizen developers to increase productivity will lead to more efficient, accurate and successful business outcomes.

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ABOUT THE AUTHOR

Alan Young 

Alan Young joined InRule Technology in 2019 as Chief Product Officer. Young leads InRule's engineering, architecture and product design teams and is responsible for translating InRule's corporate vision and strategy into product delivery.

Published Friday, December 17, 2021 7:30 AM by David Marshall
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