Advanced data science techniques, like machine learning, have proven to be extremely useful to derive valuable insights from your data. Even with a wide array of tools and technologies at their disposal, data scientists are still spending most of the time massaging and manipulating the data into a usable data asset.
Data virtualization offers a new alternative to address these issues in a more efficient and agile way. Watch on-demand this session to learn how companies can use data virtualization to:
- Create a logical architecture to make all enterprise data available for advanced analytics exercise
- Accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- Integrate popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc