Transforming security Data analytics with IBM WATSONX.Data
Use Cases and Deployment Scope
In our organisation, we use Watsonx.data as a centralized data lakehouse and analytics layer to manage, analyse, and govern large-scale operational and security-related data across a hybrid environment. We leverage this tool primarily for security operations analytics, threat intelligence enrichment, and compliance-driven reporting across multiple customers in our managed security services setup.
Pros
- Unified data access across Hybrid Environment On on-premise SQL and Oracle, FB, and cloud security data from Qradar, CrowdStrike, and Zscaler, and using this engine, analysts can query across these diverse data sets as if they were in one place.
Cons
- Integration complexity with Security Tools while watsonx.Data is well-suited for native tools, but integration with third-party security tools requires custom connectors or manual ETL pipelines. which leads to an increase in setup time.
- User interface and query time can be improved.
Likelihood to Recommend
For forensic requirements, we need to store the data for a longer duration and demand longer retention. This tool acts as a long-term data lakehouse for archived logs from multiple security tools and enables analysts to query on historical data using SQL without re-ingesting into the SIEM. and provides cost-efficient storage, and is scalable for retrospective threat hunting.