Experience The AI-Powered SAP Data Intelligence Tool
Updated January 01, 2021

Experience The AI-Powered SAP Data Intelligence Tool

Manoj Kumar Das | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with SAP Data Intelligence

  • AI-powered data extraction Software, Powered ML Engines that can transform your structured, unstructured, and streaming data into useful business insights.
  • GPU support for inference on ML models for your one premise installation.** BYOM**
  • The mode-option is for storage types that supports ADL or HDFS. Object stores such as S3 and SDL are not supported to append operation on storage level.
  • It gives opportunity to utilize OCR, ICR, IDR technology to support the business needs
  • Enhance ML capability between on-premise and cloud version.
  • The capturing of pure voice records and voice forms similar to other businesses forms of communication such as (email, web forms, fax).
  • Data integration services with other ML tools are more complex. Workflows could have been more simplified.
  • Customizing the application rather than the less available dashboards.
  • All the Management Reports, Performance Charts & Indicators, Product review information is retrieve[able] with a single click.
  • Implementation Strategy worked with 3rd-party service providers also.
SAP Data Intelligence tool could serve all our requirements out of a data intelligence tool,
Business analytics are well managed and also helps in building better business insights from a future perspective.
Integrates well with other Data Management tools already in place and helps segregate and group data from Multi-Sources and Domains using metadata catalogs.

Do you think SAP Data Intelligence delivers good value for the price?


Are you happy with SAP Data Intelligence's feature set?


Did SAP Data Intelligence live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of SAP Data Intelligence go as expected?

I wasn't involved with the implementation phase

Would you buy SAP Data Intelligence again?


We focus on standard dashboards, but the issue was that [there was] no proper visibility and monitoring available for daily reports and dashboards during deployment phase. As this little expense tool so very much focused on the limited dashboard, and is mainly for higher management.

Using SAP Data Intelligence

130 - 
  1. General management
  2. Public Relations
  3. Purchasing/Procurement
  4. Human Resources
  5. Production & Development
  6. Administration & IT Customer Care
  7. Marketing/Finance
8 - 
ISO/IEC 27001 certification
Experience in leading a team of HANA developers in design and development
Experience in SAP SLT and Business Object Data Services BODS to acquire the data into SAP
Experience in SAP HANA XSJS to expose data to other clients
Experience in interacting with business users for coordinating with them for requirement gathering

Knowledge of C++/object oriented programs, Java, web application development, security and open source technologies

• Skills for developing, deploying & debugging cloud applications
• Skills in API usage, command line interface and SDKs for writing applications
• Ability to use continuous integration and distribution pipelines to deploy applications
• Ability to code to implement essential security measures
• Familiarity with HTML/CSS, JavaScript and UI/UX design
• Excellent knowledge of UML and other modeling methods
• Experience working with databases: SQL, NoSQL, Key-value stores, etc.
• Master’s degree in Computer Science/ Computer Engineering or equivalent on-the-job experien

  • Metadata extraction for SAP S/4HANA & SAP Business Suite systems
  • Build and deploy SAP HANA Machine Learning pipelines in SAP Data Intelligence
  • Self-service and data-driven data preparation for business users
  • Transform, shape, harmonize, curate, enrich the data by a simple click
  • Create new data sets based for scenario and project requirements
  • Show sources and transformation of datasets
  • graphically from target
  • Connect lineage in data discovery (SAP LUMIRA/SAP BI/BO)
  • Tied with the connectivity and discovery from Metadata explorer
  • Define Data Quality (DQ) thresholds and monitor using
  • scorecards for key DQ KPI
  • Roadmap to tie in with data preparations
Allow collaborations among various personas
with insights as ratings and comments on the
Reuse knowledges on the datasets for new users
Next-Gen Data Management and Artificial Intelligence