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A 2022 IBM survey of 7,502 organizations revealed that about 35% of companies use AI in their business. However, 34% of these companies cited limited AI skills, expertise or knowledge as a significant barrier to adopting AI.
Deploying AI solutions - regardless of simplicity - requires technical expertise and extensive training. This limitation reduces the ability of businesses to adopt AI fast and at a cost-effective price.
However, no-code AI enables you to build AI models without extensive technical experience. It features drag-and-drop interfaces which democratize AI model development and faster time to market. This novel solution has also found its way into the data analytics industry. It enables all users to build data analysis models and generate insights quickly.
In this article, you will learn about no-code AI in data analytics, the advantages over traditional AI methods, benefits, use cases and future trends.
No-code AI in data analytics is a method that enables technical and non-technical users to build analysis models using a drag-and-drop interface. Similar to no-code in the development industry, these analytics tools offer visual elements to help you automate complex processes without writing code.
Therefore, instead of writing SQL queries or Python code, you can drag a function or predefined template and use it to extract insights from data. For example, imagine you are a retail manager who needs to analyze transactional performance and customer behavior. With a tool like Kyligence Zen, you can quickly select the retail metrics template that features essential KPIs like total sales, total transactions and more, connect your data and start analyzing.
Not only does this approach allow you to get insights fast, you also save time on defining rules using SQL or Python. No-code AI enables data analysts and non-technical users to classify, analyze data and quickly build accurate data models to get insights and make predictions.
No-code AI tools offer flexibility, accessibility and other advantages over traditional coding methods.
Traditional coding-based analytics tools often have multiple features that require a unique skill set. In contrast, no-code AI tools use a visual, drag-and-drop interface that requires minimal technical experience.
Traditional analytics tools use command and text-based interfaces that require specific queries. You must often code in Python and deal with errors and editors that are difficult for non-experts to understand. However, the no-code AI equivalent offers easy-to-use templates with instructions, making it user-friendly to a broader audience.
Most companies have to run multiple analytics models simultaneously, which requires an extra workforce if it's a time-sensitive project. With the traditional coding-based methods, you must hire different experts to complete this process faster. However, no-code AI makes it easier to reuse templates and run multiple models simultaneously without incurring additional costs.
Model development and analysis are faster with the drag & drop, templates and other codeless features of no-code AI. In contrast, traditional methods are time-consuming, especially when analyzing a large volume of data from different touch-points.
Traditional data analysis is prone to human error, affecting the data quality, result and prediction. However, using AI, you can sieve through data at higher accuracy and deliver quality insights.
Here are some benefits of adopting no-code AI business analytics tools in your organization:
Data is integral to business growth from sales, marketing, product development, customer service and more. With the no-code AI, you can customize templates for marketing insights based on your experience and expertise to suit your unique business needs. This way, you save time and always have the insights to make informed decisions. The resultant effect is a data-driven business that can predict trends. You can stay ahead by using insights generated to optimize customer service, product updates, and personalized marketing strategies.
No-code AI analytics tools allow you to use prebuilt functions and templates for analysis. One such function is the root cause found in the Kyligence Zen no-code/low-code analytics tool. This feature allows you to go beyond "what" and ask "why" specific goal performance is poor. With this feature, you can identify challenges or opportunities in real-time and create strategies for implementation. Similarly, you can identify problems in marketing, operations, and other areas and quickly make moves to mitigate the effects.
With no-code AI analytics tools, every department can access data and insights easily. They don't have to wait for the data team to collect, clean, analyze and send over a document with graphs and charts. Using no-code, business teams can study the users' behavior data to understand their expectations, trends and more. This ensures they get the correct information fast, can identify areas with the most impact, and deliver valuable products to market in record time.
No-code AI in analytics automates processes like predictive analytics, anomaly detection, data reporting and more in different industries.
No-code AI enables you to build predictive models without coding. These models help businesses in industries like restaurant operations easily forecast trends, customer behavior, and demand.
With no-code AI, you can generate automated reports and dashboards with few clicks. This saves you time on manual data analysis and presentation, which can be utilized in other productive activities.
Logistics, e-commerce, and retail businesses often deal with large inventory. Similarly, a delay or misrepresentation of data can cause significant problems meeting customer demands. With AI-powered analytics tools like Kyligence Zen, you can optimize inventory levels and supply chain operations through forecasting and demand prediction. This allows you to meet customer demands and improve overall operations.
Other use cases of no-code AI include quality control in manufacturing, web analytics in digital marketing, Healthcare analytics, and recommendation systems in entertainment.
The no-code AI industry is projected to grow at a compound annual growth rate (CAGR) of 27.3% from 2023 to 2030. This growth will usher in new implementation and use cases in different industries. Integrating no-code AI with traditional data analytics tools allows companies to maximize the benefits of both methods. Here are some future predictions and trends to note:
No-code AI in analytics offers businesses a unique solution to build fast with data-driven strategies. As the industry continues to grow, more companies will embrace this approach for its benefits like cost-effectiveness, informed decision and competitive advantage. Kyligence Zen is a no-code/low-code tool that powers data-driven solutions in many companies. It offers features that help you create a centralized analysis system accessible to all departments. You can also leverage our unique Copilot to generate insights using plain English queries. Grow your business with a quality insights analytics platform. Sign up for a free trial today.
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