Presented at World AI & RPA Show, Malaysia
To support machine learning, many organizations leverage data lakes, as they can collect large volumes of data from multiple sources, including structured and unstructured sources, and store the data in its original format. However, storing data in different formats does not necessarily facilitate discovery, as data in different formats must first be integrated before it can be leveraged for machine learning. Due to the increasingly distributed nature of data infrastructure in today’s enterprises, data integration gets more complex.
Data virtualization is a modern data integration technique that integrates data in real-time, without having to physically replicate it. It can seamlessly combine views of data from a wide variety of different data sources and feed AI/ML engines with data from a common data services layer.
Tune into this session to hear about the benefits provided by taking a logical approach to data science.