Artificial intelligence (AI) and machine learning (ML) are powering the digital transformations taking place in every industry worldwide. AI is priority for executives as it helps businesses transform the way they do business with their partner or customer network. It has become pervasive in enhancing peoples’ lives. As a matter of fact, these transformative technologies play a critical role in discovering new therapies in healthcare, alleviating risks of fraud in financial services, and providing personalized customer experiences.
For businesses at large, AI/ML-powered technologies seem like magic, while its impact is evident, they may not be aware of how to leverage these powerful innovations for the better. They must know that AI/ML technologies, especially deep learning, is heavily dependent on data. And organizations must have proper tools and expertise to leverage these data hungry mechanisms with accuracy and speed. This becomes necessary as bad data or inappropriate data-driven tools will have a huge impact on business initiatives, to the point where it has a reverse impact on the desired outcomes.
For best results, users must have a technology in place that enables them map, transform, and integrate data without seeking external support. Such self-service-powered integration solutions help businesses deal with all facets of data, from complexity to regulatory vulnerabilities. These solutions use AI, whenever required, to handle and manage data, and without such a profound foundation, AI is incomprehensible and unreliable—in other words, without a robust data integration technology, AI can be a black box that has unintended consequences.
Taking Business to a New Level
Self-service integrations packed with AI functionalities allow all business users use data-driven insights to make confident business decisions without excessively relying on IT. Not only these solutions can map and transform data faster (using AI-powered data mapping) but also integrate it into a unified database. Conventional methods, on the other hand, cannot handle voluminous information and use insightful information to drive businesses forward.
By imbibing AI, these solutions can be optimized to deliver improved execution performance. They can do so by simplifying the development lifecycle, reducing the learning time for the technology, and lowering the dependency on high skill requirement for ETL workflow creation. These solutions can train the data set to make it apt for configuration of statistical modelling on it without any manual intervention, hence alleviating the human imposed issues. Here are some advantages that these solutions promise to offer:
- The speed of data processing increases by leaps and bounds and machine learning algorithms can be leveraged by business users to map data faster, thus speeding transformations and integrations.
- The total cost of ownership and timelines reduce owing to a decrease in the usage complexity and empowerment of business users to perform the DI with less or no assistance from technical experts.
- With access to a number of pre-packaged as well as configurable data integration templates imbibed into AI, users can easily integrate data without difficulty.
- The efficiency increases as self-service integration tools with AI/ML functionalities business users can easily connect to the system and create their own data structures and application independently for any of their specific data curation and analysis needs.
Integration solutions packed with self-service and AI capabilities allow users utilize voluminous information for making informed decisions, enabling them drive ROI.