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Exam Number : ACA-BIGDATA1
Exam Name : ACA Big Data Certification
Vendor Name : Alibaba
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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 teaching

 

Alibaba to spin off its cloud, AI and enterprise messenger unit | Killexams.com Resources

Seven weeks after Alibaba introduced its ancient restructuring plan to cut up itself into six independent groups, the juggernaut is gearing up to spin off its intelligence community.

Alibaba went public in ny back in 2014, marking the largest IPO on the time. not long after Hong Kong cozy rules around twin-class constructions, which enable founders to keep certain handle whereas opening the company to outdoor investment, in 2019, Alibaba sought a secondary record within the city. Rising tensions between the U.S. and China additionally prompted many chinese language groups to retreat from the Nasdaq and NYSE in contemporary years.

“we are taking concrete steps against unlocking price from our agencies and are joyful to announce that our board has authorized a full spin-off of the Cloud Intelligence group by the use of a inventory dividend distribution to shareholders, with intention for it to become an unbiased publicly listed company,” Daniel Zhang, chairman and chief govt officer of Alibaba group, introduced in the firm’s revenue report today. Zhang is additionally probably the most cloud arm’s board of directors.

Alibaba aims to complete the spinoff within the next 12 months and plans to encompass exterior strategic investors in the community via deepest financings.

The cloud company generated $2.7 billion in income during the first quarter, making up 9% of Alibaba’s complete revenues. (My colleague Alex has a fiscal deep dive into the cloud spinout. live tuned for the story.)

You could now not be generic with Alibaba’s cloud intelligence group, however feel of its main product strains roughly as “AWS+Slack+OpenAI”.

Its cloud enterprise Alibaba Cloud dominates China’s market. Globally, Alibaba Cloud became the third greatest infrastructure-as-a-carrier (IaaS) public cloud provider in 2021, based on market research firm Gartner. Add platform-as-a-service (PaaS) and personal cloud to the mix, Alibaba came in fourth in this autumn 2021, in response to an extra market perception company Synergy analysis neighborhood.

Alibaba’s Dingtalk, an commercial enterprise chat app and productiveness platform, surpassed 600 million users as of Q3 2022, with 15 million paid each day energetic clients and 23 million enterprise clients, the enterprise noted previously.

Tongyi Qianwen, Alibaba’s flagship huge language mannequin, is at present nowhere close GPT-three’s technological prowess and have an effect on, however’s one in every of China’s most promising alternate options to the text-producing AI. It also has the talents of being utilized to an array of Alibaba products. truly, the combination has began, first with a copilot for Dingtalk.

It makes feel that Alibaba is grouping its cloud enterprise and AI analysis group beneath one umbrella as these two go hand in hand. With every new step forward in AI, the volume of computational power crucial to coach statistics raises exponentially — so does the can charge.

curiously, Alibaba mentioned in its quarterly record that it’s working to make cloud computing “more available and reasonably-priced.”

“We announced a new example family unit that provides the identical stage of steadiness and presents as much as forty% can charge discounts. For latest items, we decreased the costs of some of our core utility products, including computing, storage, networking and protection items, via up to 50%,” the business spoke of.

The timing looks apt. previous this week, Beijing unveiled a draft policy calling on cloud providers to work more intently with AI firms and guide them with all of the computing components they want.

“We agree with these moves will assist our shoppers enhance public cloud adoption in China as well as liberate rising opportunities to leverage AI technology for organisations,” Alibaba talked about.


 

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