IBM C1000-120 case studies
IBM C1000-120 · Put your knowledge to work in context.
The IBM C1000-120 certification page on IBM Training is the authoritative starting point for anyone researching this credential, but the retrieved source is a shell page that loads certification details dynamically, so no objectives, question count, time limit, passing score, fee, or validity period can be confirmed from it. What the source does establish is the surrounding program structure: IBM Professional Certification credentials are issued through IBM Training, exam registration and candidate records are handled through PearsonVUE, and issued certifications, exam history, and Mastery history appear in the My Learning profile once a candidate accepts the IBM Certification Agreement and uses an IBM ID whose name and email match the PearsonVUE record. The IBM C1000-120 case studies are 5 cases and about 2,906 words.
1Production sizing and HA for a 45 TB analytics platform
A regional insurer is deploying IBM Cloud Pak for Data 4.8 on Red Hat OpenShift 4.12 in its own data center. It has 3 control-plane nodes (16 vCPU/64 GB) and 6 worker nodes (32 vCPU/256 GB) with 12 TB of NFS-backed persistent storage.
670 words, about 3 min2Hybrid data governance across a bank with 14 business units
A bank has Db2 z/OS on-premises (1.2 PB), Oracle Exadata on-premises (300 TB), and an Amazon S3 data lake (80 TB). IBM Cloud Pak for Data 4.8 runs on OpenShift in AWS us-east-1.
616 words, about 3 min3Upgrade with 60 notebooks and deprecated custom runtimes
A retailer runs IBM Cloud Pak for Data 4.0.1 on OpenShift 4.6 with Watson Studio, Watson Machine Learning, Db2 Warehouse, and 60 Jupyter notebooks. It wants to move to CP4D 4.8.
535 words, about 3 min4Multi-tenant platform for six departments with showback
A university with six departments (research, finance, HR, student, alumni, and IT) wants one IBM Cloud Pak for Data platform for 400 users. Research needs GPU for deep learning; finance has SOX separation requirements; HR handles sensitive employee data.
523 words, about 3 min5Real-time scoring at 2,000 requests per second
A telecom wants to score 2,000 requests per second at peak with p99 latency below 50 ms using a gradient boosting model in Watson Machine Learning on IBM Cloud Pak for Data 4.8. The current CP4D environment has dev (3 workers at 16 vCPU), test (3 workers), and prod (6 workers at 32 vCPU/128 GB).
562 words, about 3 min