DSx - as a beginner
February 23, 2018

DSx - as a beginner

Bhaumik Pandya | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM Data Science Experience (DSx)

DSX is being used by a sub-department of our company.

We are using it for the projects of service-automation and recommendation systems to analyse data and build models.
  • Can connect to IBM DB2 - Data Warehouse and has integrated IDEs for Data-Scientists including RStudio, Jupyter Notebooks and SQL-Dashboard.
  • A version of DSX, DSX-Desktop, makes it quite easy to play with your data and is powered by Spark.
  • Access to ML Libs such as, Python Sci-kit Learn makes it simple to not only apply the model over data and optimize it, but also to deploy to Watson Machine Learning service for production purposes.
  • I would love to deploy the R-models for production.
  • Positive impact: Reduces effort significantly.
DSX has power of open source tools brought together in an integrated and secured environment.
Consider an ecosystem or application backend, that has different databases with different types of data (structured, documents etc.). Normally, a simple analytics for such data sources requires to fetch and query data from multiple sources and build visualizations for them. With DSX RStudio or Jupyter and DashDB (or DB2), all data can be accessed at one point. This makes it, as per the definition, a more practical approach than Data Lakes, where you can also build and deploy ML models. Almost everything that a data scientist needs.