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Exam Number : ACA-BIGDATA1
Exam Name : ACA Big Data Certification
Vendor Name : Alibaba
Update : Click Here to Check Latest Update
Question Bank : Check Questions

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ACA-BIGDATA1 exam Format | ACA-BIGDATA1 Course Contents | ACA-BIGDATA1 Course Outline | ACA-BIGDATA1 exam Syllabus | ACA-BIGDATA1 exam Objectives


Exam Specification: ACA-BIGDATA1 ACA Big Data Certification

Exam Name: ACA-BIGDATA1 ACA Big Data Certification
Exam Code: ACA-BIGDATA1
Exam Duration: 120 minutes
Passing Score: 70%
Exam Format: Multiple-choice, True/False, and Hands-on tasks
Exam Delivery: Proctored online or at a testing center

Course Outline:

1. Introduction to Big Data
- Understanding the concept of Big Data
- Exploring the characteristics and challenges of Big Data
- Overview of the Big Data ecosystem and technologies

2. Big Data Storage and Processing
- Understanding distributed file systems (e.g., Hadoop HDFS)
- Introduction to MapReduce and Apache Spark
- Exploring batch processing and stream processing frameworks

3. Data Ingestion and Integration
- Techniques for data ingestion from various sources
- Integration of structured and unstructured data
- Implementing data transformation and normalization

4. Big Data Analytics
- Introduction to data analytics and machine learning in Big Data
- Utilizing SQL and NoSQL databases for data analysis
- Implementing data visualization techniques

5. Data Governance and Security
- Ensuring data quality and data governance in Big Data projects
- Understanding data privacy and security considerations
- Implementing access control and encryption in Big Data environments

6. Big Data Infrastructure and Deployment
- Designing and configuring Big Data infrastructure
- Deploying and managing Big Data clusters
- Scaling and optimizing Big Data systems

7. Big Data Application Development
- Developing Big Data applications using programming languages (e.g., Java, Python)
- Utilizing Big Data frameworks and libraries (e.g., Apache Hadoop, Apache Spark)
- Implementing real-time data processing and analytics

Exam Objectives:

1. Understand the concepts, characteristics, and challenges of Big Data.
2. Identify and utilize Big Data storage and processing technologies.
3. Ingest and integrate data from various sources into Big Data systems.
4. Apply Big Data analytics techniques for data analysis and insights.
5. Ensure data governance, privacy, and security in Big Data projects.
6. Design, deploy, and manage Big Data infrastructure.
7. Develop Big Data applications using programming languages and frameworks.

Exam Syllabus:

Section 1: Introduction to Big Data (10%)
- Concept and characteristics of Big Data
- Challenges and opportunities in Big Data projects
- Overview of the Big Data ecosystem and technologies

Section 2: Big Data Storage and Processing (20%)
- Distributed file systems (e.g., Hadoop HDFS)
- MapReduce and Apache Spark for data processing
- Batch processing and stream processing frameworks

Section 3: Data Ingestion and Integration (15%)
- Techniques for data ingestion from various sources
- Integration of structured and unstructured data
- Data transformation and normalization

Section 4: Big Data Analytics (15%)
- Data analytics and machine learning in Big Data
- SQL and NoSQL databases for data analysis
- Data visualization techniques

Section 5: Data Governance and Security (10%)
- Data quality and data governance in Big Data projects
- Data privacy and security considerations
- Access control and encryption in Big Data environments

Section 6: Big Data Infrastructure and Deployment (15%)
- Designing and configuring Big Data infrastructure
- Deployment and management of Big Data clusters
- Scaling and optimization of Big Data systems

Section 7: Big Data Application Development (15%)
- Big Data application development using programming languages
- Utilizing Big Data frameworks and libraries
- Real-time data processing and analytics



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Alibaba headquarter

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What else am i able to say about Alibaba (NYSE:BABA)? it's been one of my worst-performing holdings. over the last several years, the China boom story did not play out how i believed it would as geopolitical and macroeconomic headwinds drastically impacted the funding narrative. Shares of BABA peaked at round $309.ninety two on October 19th, 2020, and just over three years later, BABA has fallen -seventy five.ninety one% (-$235.26). I do not get everything appropriate, and that i have watched shares of BABA drastically decline in disbelief. I started a position in the iciness of 2021 as shares were in the beginning declining. due to the fact that beginning the position, I actually have paid about as lots as $250 for shares and currently as low as $seventy five. I've gotten my cost basis to round $one hundred forty four, and i am considering that adding sufficient shares while its share rate is below $80 to get my charge foundation to around $one hundred. this is the actual explanation why i'm particularly different and hold money on the sidelines. I went into BABA knowing that things could go incorrect and that shares may also now not rebound anytime quickly. There hasn't been a minute of lost sleep over the unrealized loss as BABA is a comparatively small place for me, and that i could add extra capital each time i needed. whereas I even have been fully flawed on how this investment would turn out, BABA is a strong enterprise with massive growth on the horizon. i am not dropping by the wayside and am making a decision to undergo whatever comes next, as BABA has the expertise to nevertheless be a pretty good investment for me.

BABA

in the hunt for Alpha

Following up on my old article about Alibaba Alibaba has been a destroyer of capital for me, but i am not willing to cut my losses Alibaba continues to trade at a ridiculously low valuation BABA

Steven Fiorillo, in quest of Alpha

FCF

Steven Fiorillo, in search of Alpha

EPS

Steven Fiorillo, looking for Alpha

EPS

in quest of Alpha

Revenue

searching for Alpha

Alibaba is beneficial shareholders through buybacks and now a dividend Dividend

looking for Alpha

hazards to my investment thesis Conclusion
 

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