AWS Certified Data Analytics – Specialty” is a high-level certification provided by Amazon AWS. This credential recognizes people working in the field of data analytics. To obtain this certification, applicants must pass an exam administered by Amazon AWS. In this section, go through the test and how to prepare for it in order to obtain this industry-recognized certificate.
AWS's data analytics ecosystem provides a bewildering number of tools and services. Here are a few examples of the topics cover in depth:
- AWS Kinesis is used to stream enormous amounts of data.
- Message Queuing using Simple Queue Service (SQS)
- Managing the onslaught of data from the Internet of Things (IOT)
- Using the AWS Database Migration Service to migrate from modest to large amounts of data (DMS)
- Using the Simple Storage Service to store enormous data lakes (S3)
- Using DynamoDB to optimize transactional queries
- Using AWS Lambda to connect your large data systems
- AWS Glue, Glue ETL, Glue DataBrew, Glue Studio, and Lake Formation make unstructured data queryable.
- Elastic MapReduce can process data at any scale, including Apache Spark, Hive, HBase, Presto, Zeppelin, Splunk, and Flume.
- Deep Learning, MXNet, and Tensorflow are being used to apply neural networks at a vast scale.
- Using Amazon SageMaker to apply complex machine learning algorithms at scale
- Kinesis Analytics is used to analyze streaming data in real time.
- Amazon OpenSearch (previously Elasticsearch) Service for searching and analyzing petabyte-scale data
- Using Amazon Athena to query S3 data lakes
- Redshift and Redshift Spectrum are used to host large-scale data warehouses.
- Using the Relational Database Service (RDS) and Aurora, you may integrate smaller data with your large data.
- QuickSight allows you to interactively visualize your data.
- Encryption, KMS, HSM, IAM, Cognito, STS, and other security features keep your data safe.
- Increase your chances of passing the AWS Certified Data Analytics Specialty test by following these steps.
- With Kinesis, you can move and alter huge data streams.
- Store large amounts of data in a scalable and safe manner using S3 and DynamoDB.
- AWS Lambda and Glue ETL are used to process large amounts of data.
- Using Elastic MapReduce, connect the Hadoop ecosystem to AWS.
- Use Amazon ML, SageMaker, and deep learning to apply machine learning to large data sets.
- Kinesis Analytics, Amazon Elasticsearch Service, Redshift, RDS, and Aurora may be used to analyze large amounts of data.
- Using AWS QuickSight, see large amounts of data in the cloud.
Exam Format and Information
AWS Certified Data Analytics Specialty
English, Japanese, Korean, and Simplified Chinese
Multiple Choice and Multi-Response Questions
Number of Questions
750 (on a scale of 1-1000)
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AWS assesses many sorts of abilities with a person through the test to offer this certificate. The primary focus is on determining the candidate’s ability to design various AWS-based data analytics services that can be integrated into the data lifecycle of collection, storage, processing, and visualization. It also evaluates the applicants’ comprehension of how various AWS data analytics services interface with one another.
The test questions are divided into the following domains. The weightage of each domain is assigned to each of them.
- Collection (18%)
- Storage and Data Management (22%)
- Processing (24%)
- Analysis and Visualizations (18%)
- Security (18%)
The inquiries in the preceding domains are largely about AWS services. For example, questions in the storage and data management area will be about various AWS products and services for storage and data management, as well as how to apply them in various use cases.
- Determine the collecting system’s operating characteristics.
- Select a data collecting system that can manage the data’s frequency, volume, and source.
- Choose a collection system that addresses essential data attributes such as order, format, and compression.
- Determine the operational features of an analytics storage solution.
- Analyze data access and retrieval patterns
- Choose a suitable data layout, schema, structure, and format.
- Establish a data lifecycle based on consumption patterns and business needs.
- Select a suitable system for classifying data and maintaining metadata.
- Determine the requirements for an effective data processing solution.
- Create a solution for data transformation and preparation for analysis.
- Automate and deploy a data processing solution
- Determine the operational features of a solution for analysis and visualization.
- Choose the best data analysis solution for a specific case.
- Choose the best data visualization solution for a specific case.
- Determine the best authentication and authorization techniques.
- Use data security and encryption mechanisms.
- Implement data governance and compliance safeguards
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Frequently Asked Questions
$300 USD, plus any applicable taxes.
180 minutes to finish the exam.
This test is accessible in the following languages: English, Japanese, Korean, and Simplified Chinese.
AWS Certification helps learners gain credibility and confidence by confirming their cloud skills with an industry-recognized certificate, and it also helps companies discover talented employees to drive AWS cloud projects.
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