Data is at the heart of the success of any modern business. However, the recent exponential growth of enterprise data has been accompanied by an equally drastic increase in complexity: more processes, ever more data sources, and a constant march toward new ways to leverage it all. .
This data can also be one of the company’s most valuable assets. However, realizing its potential requires more than a team of human analysts can accomplish. Getting the most out of your data requires AI-powered data analytics.
What is AI data analysis?
AI Data Analytics is the process within business intelligence (BI) that automates the analysis of large amounts of business data using artificial intelligence (AI) and machine learning software. By using an AI analysis tool rather than human analysts, data analysis can be faster and patterns and other information can be discovered that a human operator would likely not be able to detect.
What are the benefits of AI-based data analysis?
Speed
Removing the human element from the data analysis process significantly increases the speed at which data is analyzed. But speed alone isn’t the only advantage: it’s what an organization’s employees can do with the data that creates real opportunities. Everything from marketing campaigns to factory operations can be automated through the use of AI-driven data analytics, removing bottlenecks and other delays inherent to human intervention.
Precision
Analyzing large amounts of data can be tedious, and boredom breeds mistakes, even for the most careful people. In contrast, AI-based data analysis ensures the same level of precision for every bit of data, from start to finish. Costly errors due to human error can be eliminated and the results of AI-based data analysis can be trusted even for the most sensitive business scenarios.
Preview
When data analysis is driven by AI, the field of vision expands beyond what the human brain can understand. With this expanded view, AI analytics systems can detect patterns in data that human operators would miss. These models can then be transformed into actionable insights that human employees can use to make smarter, more strategic business decisions.
AI analytics requires ubiquitous connectivity
To achieve fully AI-driven data analysis, your organization must adopt a ubiquitous connectivity approach to data management. Simply put, pervasive connectivity is the interconnection of every data source and endpoint within an organization.
Without access to all the data flowing through your organization, an AI-based analytics system will not be able to operate fully effectively. By connecting every point where data enters your organization and informs its operations, you can be sure that everyone, including the AI analytics system, is working with the most up-to-date information.
Boomi enables AI-driven data analytics
Boomi Master Data Hub, intelligent flow process integration and intelligent connectivity based on connectors and APIs ensure data discovery and standardization. These tools and processes make it easy to break down data silos, protect data, and make it available for advanced analytics.
Achieving competitive advantage through successful AI analytics is possible when you use Boomi’s intelligent connectivity and automation to ensure successful data discovery, capture, cataloging and normalization while ensuring intelligent process integration keys that consume them.
For more information, see Boomi’s executive brief, AI, data analytics and the pressure to be more competitive.
