C1000-190 sample questions

Question 1

Background:
A global logistics company is migrating its legacy analytics workloads to IBM watsonx.data. They process 50TB of telemetry data daily from their delivery fleet.

Current Situation:
Currently, all data is stored on high-performance block storage, which is becoming prohibitively expensive. The data science team queries the last 7 days of data heavily for predictive maintenance models. The BI team runs monthly summary reports on data up to 1 year old. Compliance regulations require all raw data to be retained for 7 years, though data older than a year is rarely accessed.

Requirements:
The Chief Data Officer requires a storage architecture that minimizes costs while meeting the performance SLAs for the data science and BI teams. They want to implement a data tiering strategy using the lakehouse.

Which of the following data tiering strategies is the MOST optimal implementation for this scenario?

Accepted Answer

Place the 7-day data on high-performance block storage (Hot), the 1-year data on Cloud Object Storage Standard tier (Warm), and the 7-year data on Cloud Object Storage Archive tier (Cold).

Answer

Keep the 7-day data in a traditional data warehouse (Hot), move the 1-year data to a data lake (Warm), and delete the 7-year data to save costs (Cold).

Answer

Store all 7 years of data on Cloud Object Storage Standard tier to ensure the BI team has uninterrupted access to historical data at all times.

Answer

Utilize Apache Spark memory for the 7-day data (Hot), local NVMe drives for the 1-year data (Warm), and tape backups for the 7-year data (Cold).

Question 2

When implementing an ingestion strategy for a data lakehouse, an organization decides to shift from traditional ETL to an ELT approach. What is the primary operational advantage of this shift in the context of IBM watsonx.data?

Accepted Answer

Raw data is immediately available in the lakehouse storage layer, and transformations leverage the lakehouse's scalable compute engines (like Spark or Presto) when needed.

Answer

It forces transformations to occur on a dedicated middle-tier server before data reaches the lakehouse.

Answer

It eliminates the need for metadata catalogs since transformations are applied sequentially.

Answer

It requires data to be converted into proprietary warehouse formats prior to loading, enhancing security.

Question 3

Which TWO of the following are core benefits of utilizing a data lakehouse architecture compared to maintaining separate data lakes and data warehouses? (Select TWO)

Accepted Answer

Elimination of redundant data copying between isolated storage systems

Accepted Answer

Support for both structured BI queries and unstructured machine learning workloads on the same platform

Answer

Requirement to use proprietary, vendor-locked data formats for performance

Answer

Tighter coupling of compute and storage to ensure strict hardware alignment

Answer

Automatic translation of unstructured data into relational tables upon ingestion without metadata

Question 4

True or False: In a data lakehouse architecture utilizing open table formats like Apache Iceberg, schema evolution (such as adding, renaming, or dropping columns) requires a full rewrite of the underlying data files.

Accepted Answer

False

Answer

True

Question 5

When configuring the storage layer for a watsonx.data implementation, which protocol must the underlying Cloud Object Storage support to ensure seamless integration?

Select the correct protocol to complete the sentence: The object storage must be _____-compatible.

Accepted Answer

S3

Answer

NFS

Answer

SMB

Answer

HDFS

Question 6

During a performance review, an engineer notices that queries against the data lakehouse are slower than expected. Upon investigation, they find that the metadata catalog is experiencing severe latency.

What role does the metadata/catalog layer play in a lakehouse architecture that makes it critical for query performance?

Accepted Answer

It tracks file locations, schemas, and statistics, allowing the compute engine to prune unnecessary files during query planning.

Answer

It caches all raw data files in memory before returning them to the compute engine.

Answer

It acts as the primary compute engine that executes SQL statements before pushing results to Presto.

Answer

It physically moves cold data to warm tiers dynamically based on incoming query volume.

Free C1000-190 sample questions

When implementing an ingestion strategy for a data lakehouse, an organization decides to shift from traditional ETL to an ELT approach. What is the primary operational advantage of this shift in the context of IBM watsonx.data?

Which TWO of the following are core benefits of utilizing a data lakehouse architecture compared to maintaining separate data lakes and data warehouses? (Select TWO)

True or False: In a data lakehouse architecture utilizing open table formats like Apache Iceberg, schema evolution (such as adding, renaming, or dropping columns) requires a full rewrite of the underlying data files.

When configuring the storage layer for a watsonx.data implementation, which protocol must the underlying Cloud Object Storage support to ensure seamless integration? Select the correct protocol to complete the sentence: The object storage must be _____-compatible.

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