The Alibaba ACA Big Data exam preparation guide is designed to provide candidates with necessary information about the ACA-BigData1 exam. It includes exam summary, sample questions, practice test, objectives and ways to interpret the exam objectives to enable candidates to assess the types of questions-answers that may be asked during the Alibaba Big Data (ACA) exam.
It is recommended for all the candidates to refer the ACA Big Data objectives and sample questions provided in this preparation guide. The Alibaba ACA-BigData1 certification is mainly targeted to the candidates who want to build their career in Big Data domain and demonstrate their expertise. We suggest you to use practice exam listed in this cert guide to get used to with exam environment and identify the knowledge areas where you need more work prior to taking the actual Alibaba ACA Big Data exam.
Alibaba ACA Big Data Exam Summary:
|
Exam Name
|
Alibaba ACA Big Data (ACA-BigData1) |
| Exam Code | ACA-BigData1 |
| Exam Price | $120 USD |
| Duration | 90 minutes |
| Number of Questions | 60 |
| Passing Score | 65 / 100 |
| Recommended Training / Books | Big Data Exam Preparation Course |
| Schedule Exam | PEARSON VUE |
| Sample Questions | Alibaba ACA Big Data Sample Questions |
| Recommended Practice | Alibaba Big Data (ACA) Practice Test |
Alibaba ACA Big Data Syllabus:
| Section | Objectives |
|---|---|
| Base of distributed theory: |
- Know about the basic distributed system theory, like the concept of distributed file system and distributed computing framework. - Know how the common components in Hadoop ecosystem work, e.g. distributed file system (HDFS), computation framework (MapReduce), resource management component (YARN) and resource coordination component (Zookeeper). |
| E-MapReduce: |
- Familiar with the basic concepts of each component of EMapReduce, including YARN, Spark, Zookeeper, Kafka, etc. - Familiar with instance type, Auto Scaling features, Jindo Filesystem, common application scenarios and pricing model. |
| MaxCompute: |
- Familiar with big data computing services basic concepts, including project, table, partition, resources, task, etc. - Understand big data computing services including the composition of the structure and function of each component. - Master the characteristics, advantages and application scenarios of Alibaba Cloud big data computing services. - Know how to connect and use the computing services, including the use of client odpscmd, management console, Java SDK, etc. - Know how to do the big data computing service data upload and download, can use tunnel command line tools, understand the Tunnel SDK. - Familiar with user-defined functions, including UDF, UDAF, and UDTF, able to write simple custom functions. - Understand the Graph programming framework, including basic concepts, processing procedures, can write a simple Graph program. - Familiar with the concept and practical operation of the security and permission management of MaxCompute, including users, roles, authorization (ACL & Policy), project space protection, external and security level, etc. |
| DataWorks: |
- Familiar with the basic functions of DataWorks, including data Integration, data studio, data servie, operation & maintenance center, organization management and project management. - Understand the basic features of DataWorks, including role isolation, environment isolation, etc. - Has knowledge about how to leverage project management and organizational management modules to build data analysis environment. - Proficient in the design and development of data development module of DataWorks, including construction table, task development, resource upload, data upload, new functions, etc. - Able to use DataWorks' data development module for workflow task and node task development and design, can configure appropriate dependencies and periodic scheduling. - Able to use the data management module for data management, including linage analysis, application and authorization of use of objects, etc. - Able to fix the basic problems by identifying and locating the problems in the process. |
| Quick BI: |
- Has knowledge about workflow of how to use Quick BI get better insight of data. - Know how to create dataset, create workbook, data modeling and create report tables. |
| DataV: | - Know how to manage data source, manage project, canvas setting and manage widgets in DataV. |