Summary

Managing data effectively is really important for saving time, cost, and complexity for every organization. A machine learning practitioner should be aware of the best options for transferring, storing, and transforming data to build machine learning solutions more efficiently. In this chapter, we learned about multiple ways of bringing data into the Google Cloud environment. We discussed the best options for storing it based on the characteristics of the data. Finally, we discussed multiple different tools and methods for transforming/processing data in a scalable manner.

After reading this chapter, you should feel confident about choosing the best option for moving or transferring data into your Google Cloud environment based on the requirements of the use case. Choosing the best place to store data and the best strategy to analyze and transform data should be easier as we now know the pros and cons of different options. In the next chapter, we will deep dive into Vertex...