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IBM C2090-101 Exam Overview:
| Certification Vendor: | IBM |
|---|---|
| Exam Name: | IBM Big Data Engineer |
| Exam Number: | C2090-101 |
| Exam Price: | 200 USD |
| Real Exam Qty: | 53 |
| Available Languages: | English |
| Certificate Validity Period: | 3 years |
| Passing Score: | 65% |
| Related Certifications: | IBM Analytics: Platform Analytics |
| Exam Duration: | 75 minutes |
| Exam Format: | Multiple-choice questions, Single/multiple answer |
| Recommended Training: | IBM BigInsights Foundations Hadoop and Big Data Essentials |
| Exam Registration: | IBM Certification Portal Pearson VUE Registration |
| Sample Questions: |  |
| Exam Way: | Proctored online or onsite at Pearson VUE test centers |
| Pre Condition: | No formal prerequisites; recommended 1-2 years of hands-on experience with Hadoop, IBM BigInsights, Hive, Pig, HBase, and SQL |
| Official Syllabus URL: | https://www.ibm.com/certify/exams/C2090-101 |
IBM C2090-101 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Security | 8% | - Monitor and secure sensitive data - Apply data masking and redaction techniques - Comply with security standards (PCI, PII protection) - Implement access control and LDAP security |
| Topic 2: Performance and Scalability | 15% | - Tune Hive, HBase, and Big SQL performance - Apply best practices for latency and throughput - Ensure high availability and scalability - Optimize query execution and workload management |
| Topic 3: Architecture and Integration | 17% | - Ensure consistent processing with InfoSphere Streams - Design cluster architecture and storage layers - Evaluate use cases for Hive, Big SQL, and HBase - Implement MapReduce and RDD concepts - Integrate GPFS and distributed file systems |
| Topic 4: Data Preparation, Transformation, and Export | 26% | - Apply Jaql for data manipulation - Export results from Hadoop environment - Create BigSheets workbooks - Perform entity resolution and data cleansing - Use Pig for data transformation |
| Topic 5: Data Loading | 34% | - Extract data from relational sources using Sqoop - Load unstructured data into InfoSphere BigInsights - Load log files with Flume and command-line tools - Create Big SQL tables and load data into Hadoop - Ingest data into HBase and Hive - Import streaming data using InfoSphere Streams |
IBM C2090-101 Exam: FAQ for Serious Candidates
IBM Big Data Engineer is an official IBM exam, listed under exam code C2090-101. A passing result earns you the IBM Certified Data Engineer – Big Data certification at the Professional level. It also ties into IBM Analytics: Platform Analytics, extending its value across your certification roadmap. Employers read this credential as verified competence, which is why it keeps appearing in job requirements.
Expect 53 questions inside 75 minutes on the IBM Big Data Engineer exam. That pace punishes hesitation, so rehearse it: the ActualPDF software engine simulates the real exam scene, reminds you of the questions you got wrong, and pushes you to re-practice them until the clock stops being your enemy.
Passing IBM Big Data Engineer requires 65%, and the official registration fee is 200 USD. Retakes charge the full 200 USD again, which is why experienced candidates treat preparation as the cheaper exam fee. Verify your readiness with repeated ActualPDF practice scores above the requirement before you commit to a date.
No formal prerequisites; recommended 1-2 years of hands-on experience with Hadoop, IBM BigInsights, Hive, Pig, HBase, and SQL
Requirements evolve, so confirm the current conditions before registering on the official exam page.
Registration for IBM Big Data Engineer goes through the official channels listed here.
When you schedule, note that the exam is delivered Proctored online or onsite at Pearson VUE test centers.
IBM recommends the following training for IBM Big Data Engineer candidates.
Follow any course with the 108 practice questions in the ActualPDF C2090-101 package; the software engine will even remind you which mistakes need another round.
Yes. ActualPDF provides a free download demo of the IBM Big Data Engineer material, so you can check the content before choosing a version. After purchase, a one-year warranty covers you: the latest version is sent to you as it releases, free for 365 days, and after expiry you can extend the update service at a 50% discount.
Your purchase is covered by a 100% money-back guarantee with clear conditions. Take the IBM Big Data Engineer exam within 60 days of purchase; if you fail, provide your unqualified result by submitting a scanned enrollment slip and the official Score Report PDF within 2 days of the exam, and the full refund is processed within 7 days. The exam must match your product, candidate and payer names must match, and attempts within 3 days of purchase, unused downloads, free materials, and expired orders are not covered. Alternatively, exchange for two other exam products of equal value, free, or wait for updates while keeping your original product's update service.
Delivery is instant: files unlock for download at payment and are emailed within one minute. If nothing arrives within 2 hours, check spam and contact customer service, which works 7/24 and normally replies within two hours. Installation is unlimited across your computers.
The IBM Big Data Engineer syllabus spans 5 domains, led by Data Preparation, Transformation, and Export (26%), Data Security (8%), and Architecture and Integration (17%). The complete topic list is published above; candidates who study the map first rarely get lost later.
IBM Big Data Engineer Sample Questions:
What is the primary purpose of Flume in the Hadoop ecosystem?
- A. To stream data from Hadoop
- B. To move static files from the local file system into HDFS
- C. To import data from a relational database or data warehouse into HDFS
- D. To capture log data as it is written to log files and move them into HDFS
Correct Answer: C 🗳️
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Which of the following statements regarding Big SQL is TRUE?
- A. Big SQL can be deployed on a subset of data nodes in the BigInsights cluster
- B. Big SQL provides a SQL-on-Hadoop environment based on map reduce
- C. Big SQL doesn't support stored procedures
- D. Only tables created or loaded via Big SQL can be accessed via Big SQL
Correct Answer: A 🗳️
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Which is a benefit of row oriented table design?
- A. When columns of a single row are required at the same time, the entire row can be retrieved with a single disk seek regardless of row size
- B. When writing a new row, if all of the row data is supplied at the same time the entire row can be written with a single disk seek
- C. When an aggregate needs to be computed over many rows but only a notably smaller subset of all columns of data, reading that smaller subset of data can be faster than reading all data
- D. When new values of a column are supplied for all rows at once, that column data can be written efficiently and replace old column data without touching any other columns for the rows
Correct Answer: A 🗳️
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Which of the following statements regarding importing streaming data from InfoSphere Streams into Hadoop is TRUE?
- A. Big SQL can be used to preprocess the data as it flows through InfoSphere Streams before the data lands in HDFS
- B. Streams applications never need to be concerned with making the data schemas consistent with those on Hadoop
- C. InfoSphere Streams can both read from and write data to HDFS
- D. The Streams Big Data toolkit operators that interface with HDFS uses Apache Flume to integrate with Hadoop
Correct Answer: A 🗳️
Which of the following statements regarding Sqoop is TRUE?
- A. When exporting data back to a database, a target table will be created if it doesn't already exist
- B. The import of a single database table results in multiple files in HDFS
- C. Sqoop processes the entire database table as a single unit rather than row-by-row for enhanced performance
- D. Output files are always delimited text files in HDFS
Correct Answer: D 🗳️
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