Big Data Modeling Challenges and Machine Learning with No Code

What are the Big Data model challenges in today's field? With a few best practice recommendations and Machine Learning approaches, I will use Knime to show the modeling advantages for Big Data with the following themes:

.Performance: Good data models can help us quickly query the required data and reduce I/O throughput.
.Cost: Good data models can significantly reduce unnecessary data redundancy, reuse computing results, and reduce the storage and computing costs for the big data system.
.Efficiency: Good data models can greatly improve user experience and increase the efficiency of data utilization.
.Quality: Good data models make data statistics more consistent and reduce the possibility of computing errors.

I will also describe tools for Sources, Ingestion, Exploration, Modeling and Machine Learning.

Speaker: Karthikeyan Chinnusamy, Veritas Technologies