When it comes to storing data, sometimes less is more.

Today, we have more data to manage than ever. We also have better algorithms that help us access our data faster. Cloud is the driving force behind many of the data warehouse advancements we have enjoyed in recent years. But what are the best practices for storing data in the cloud for machine learning and data science applications?

In this webinar, Alex Lovell-Troy, Pythian’s Vice President of Transformation Services, discusses how to manage large volumes of data in the cloud. You will learn about:

• Data hoarding and legacy data
• Transforming data through data pipelines
• Data science “janitorial work”, or  cleaning up your data sets
• The value of data at rest and data in motion
• Migrating to the cloud to meet regulatory standards
• What happens to unused data over time