Why use Watson Explorer for Data Science Experience

Transform unstructured data into structured data

Since 80 percent of enterprise data is unstructured, transforming it to structured data is critical for data-driven enterprises. Create a holistic view of all your data, not just structured data, with natural language processing and content mining to improve decision making. Drive intelligent actions and scale expertise to more broadly enable better business outcomes.

Discover key trends and insights from text data

Extract information from text so that it can be handled as structured data, with key information identified and categorized through annotation. Compute statistical scores such as frequency and collocations of extracted keywords. Annotations are stored in a text index and statistical scores — correlations, trends, confidence intervals — are computed and visualized, so you can understand the characteristics of information in text data.

Combine data types to optimize resources

Use content mining to refine information extraction and help standardize unstructured data along with structured data. Together, all of your data can be explored using the visual and command-line data analysis tools of Data Science Experience. Bringing your data sources together eliminates guesswork and effort to optimize resource utilization and decrease time to value.

Enable seamless information sharing across tools

Work in tandem with other data science tools. You can use Jupyter notebooks alongside IBM SPSS® to drag and drop visualization tools for a robust view of your information. Integrate with IBM Decision Optimization and IBM SPSS Modeler solutions to explore possible trends or insights. Because specialized add-ons like Watson Explorer can extend Data Science Experience, its capabilities can be tuned to your organization’s specific needs.

Simplify access to data science analysis tools

An intuitive interface makes it easy to visualize your data. Traditional text processing applications and strategies are limited by the need for specialized expertise and carefully tailored data. With Watson Explorer, you can extend an analysis to unstructured data using visual capabilities and engage both novices and experts. Enabling natural language processing for intuitive mining gives a broader group of users the power to gather insights and construct detailed queries of their own.

Cut deployment time using IBM solutions in tandem

The IBM combination of open standards-based Apache UIMA text analytics alongside natural language processing and content mining capabilities delivers a unique environment for detecting patterns in unstructured data. When used with an operation-ready, scalable solution like IBM SPSS Modeler, Watson Explorer for Data Science Experience helps you reduce deployment time from months and weeks to days.

Unlock the power of your organization’s hidden data

Read the solution brief

Technical details

Software requirements

Supported operating systems:

  • Red Hat Enterprise Linux (RHEL) 6.5: Minimum install
  • Red Hat Enterprise Linux (RHEL) 7: Base minimum install

Hardware requirements

See system requirements for Data Science Experience Local at link. Add 2 CPU and 4 GB of memory for each Data Science Experience project. Add 0.5 CPU and 2 GB of memory for each Watson Explorer collection. Add 2 CPU and 4 GB of memory for each model using Watson Explorer capability.

  • x86-64
  • Bitness: 64-Exploit
  • Disk storage: 10 GB for installation