Analytics Trends To Watch In 2022

Posted by LPA Software Solutions on Nov 8, 2021 12:07:06 PM

10 Trends in Business Analytics for 2022

2020-2021 was a pivotal period of digital transformation for organizations of all sizes globally, unequivocally due to the pandemic. Along with that surge is a greater interest in and use of business analytics and artificial intelligence. Both have proven to have real-world and real ROI implications that more and more organizations are using to make sound strategic business decisions.

With that in mind, here is a roundup of the 10 Analytics and Artificial Intelligence trends to watch in 2022.

1. Mobile Access

Mobile access is absolutely a requirement for the modern world. From remote employees to customers accessing online systems, mobile access has evolved from a trend to a necessity. Analytics applications must be mobile enabled to meet the demands of businesses, employees and customers who are accessing information on the go and need to make quick decisions based on that information. Mobile access also gives employees the same tools that they previously had to go into the office to use no matter where they are in the world.

10 Trends in Business Analytics for 2022: Data Governance

2. Continued SaaS and Cloud Adoption

Cloud computing and remote work on a global scale fueled the massive migration to software-as-a-service (SaaS) and cloud computing. With the investment made, organizations are not going to go backwards, and that also goes for business analytics and artificial intelligence.

The demand for cloud based business intelligence is keeping pace with the demand for other types of cloud based applications. Organizations are investing in public and private clouds and SaaS solutions. The benefits of cloud are simplified administration and maintenance, less costly than on premise solutions, greater scalability, as well as data security, backup, and disaster recovery.

3. Data Governance

Remote work, mobility, compliance requirements, and increases in cyber threats will continue to prioritize data governance highly. The number of data sources are increasing in number as well as complexity. Data governance policies are absolutely critical to manage data accuracy and consistency to maximize the return on your analytics program.

4. Collaboration

As organizations tap into and harness analytics insights, collaboration is the next logical step. Dashboards, shareable reports, and features like commenting, mentions, and tagging engage users and make collaboration easier than ever.

5. Automation

Smart leaders will use automation to reduce the time spent on manual, repetitive processes. Automation increases productivity as well as the accuracy of the output. Employees have more time for higher value tasks and projects.

According to Analytics Insight, “Data automation, also known as hyper-automation, is one of the most disruptive technologies for the year 2022. 40% of all data science related processes will be automated by the end of the year, making data automation a BI trend to watch in 2022.” 

6. Data Literacy and Data-Driven Cultures

Interpreting data and developing insights requires a foundation of data literacy. Organizations must understand how to evaluate data points and ask the right questions to best use their data to drive strategic decisions. Data literacy may require training. Sometimes a cultural shift is needed to fight the tendency to do things the way they’ve always been done. The decision to trust the data and use it to make strategic decisions must come from the top down.

Female finger touching a beam of light surrounded by charts and graphs7. Artificial Intelligence

Even in small businesses, AI can bring great efficiencies and more sales. Companies can incorporate chatbots into their customer service and collect valuable data from customer service interactions. Converting that data into insights that can drive customers to buy more when presented with information as simple as “Show me more like this” and “People who bought this also bought.”

Other organizations use artificial intelligence to comb through virtual mountains of unstructured data to serve up relevant information to employees through easy natural language searches.  

Machine learning algorithms, advanced neural networks, and augmented analytics can help manufacturers detect parts that may be slightly out of scope and imaging technicians discover anomalies in medical scans.

8. Natural Language Processing

Anyone who has asked a question of Siri or Alexa has experienced a learning curve in asking questions for more accurate AI results. With natural language processing BI solutions, users can ask questions as if they’re asking a colleague. Such is the accuracy of machine learning and natural language processing, and yes, voice activated digital assistants will get better with Natural Language Understanding/Prossessing to deliver more relevant results.

9. Data Storytelling and Data Visualization

Attention spans have continued to shorten. Data visualization and storytelling combat dimishinging attention spans and raise engagement with information. Data storytelling puts information into a narrative context, including dashboards and interactive reports. Graphs and charts help users understand the information they may not have easily comprehended when presented in text and numbers. Expect BI vendors to focus on dashboards and visualizations for data storytelling.  

10. Self-Service

Usability and accessibility are hallmarks of applications, and BI tools are no different. Even executives with little free time and analytics skills want direct access to user friendly reports and dashboards, where they can drill down into information and run ad-hoc reports. Self-service BI reduces reliance on IT developers and gives access to users.

All of the AI and BI trends for 2022 and beyond closely follow computing and application trends. User friendliness and accessibility remain the most significant drivers. To explore the possibilities for your organization with AI and BI, contact LPA today or take our complementary assessment.

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Topics: Data Science & AI, AI, Unstructured Data, Analytics, Data Science, Trends