If we explore any Artificial Intelligence (AI), data is the fuel that powers today's development and deployment of those intelligent systems. However, the process of gathering and ingesting data for those complex systems poses a unique set of challenges. With the diversity of data sources, increasing complexity as well as a primary need to maintain data quality and consistency, the data gathering and ingestion process has become a critical factor for AI development. In this blog, we will explore the challenges commonly faced by businesses and organisations while gathering and ingesting data for an AI model. Along with that, we will discuss the best practices for overcoming these challenges and ensuring the effective use of data in AI development.
The challenges faced during the Data Gathering and Ingestion process are as follows:
The challenges mentioned above might not include all the challenges encountered during any specific project as each project have their own sources and way of collecting data. The ingestion platform and methodology also might differ from project to project. If we compare these challenges to the ones we encountered during the creation of our own AI Image Process Automation (IPA) solution, there would be additional challenges such as:
In conclusion, the process of gathering and ingesting data for AI presents a range of challenges for businesses and organizations. However, by investing in robust data cleaning and normalization processes, advanced data integration tools and techniques, scalable data infrastructure and architecture, and robust data privacy and security measures, organizations can overcome these challenges and effectively leverage data for AI development. With the right approach, businesses can transform data from a challenge into a powerful tool for innovation and growth.
Net Reply is a company that has experience in Network Automation, Cloud Connectivity and Artificial Intelligence. If you would like to know more about the AI Image Process Automation (IPA) tool, or be given a demo, please reach out to us LinkedIn or contact the author of this article,