Especificaciones de test
David Clinton
Idioma(s) Disponibles:








20 questions

Límite de tiempo sugerido:

36 minutes


Processing data

Collecting and storing big data

Analyzing data


AWS for Data Analysis Professionals Assessment Test: How it is structured and how it can help you hire your best candidate

This test was designed to help anyone evaluate anyone’s competency in AWS when it comes to Data Analysis Professionals. AWS covers a wide range of expertise and data analysis is one of the core tasks that require experience and knowledge. It is important that this facet of the AWS competency is assessed specifically for a job position that would require this expertise.

By using this assessment test, you can have the confidence of being able to identify a candidate’s knowledge of the subject matter. This in return will help you make informed hiring decisions.

Which use cases can customers have for this test?

Just about everyone has big data that needs analyzing. AWS has a solid set of inexpensive and efficient tools for managing and analyzing data at any volume. There are always multiple ways to perform a given data-based task on AWS and the features of many of its services overlap with others. As such, it’s unlikely that anyone with the data proficiency will be an expert on all AWS data services. However, you’ll want to understand their knowledge of the basics to identify which is the best use case for different requirements.

¿Qué áreas (capítulos) se cubrirán en la prueba y por qué se eligió de esa manera?

Processing data
Understand how to use Amazon EMR to leverage the power of Hadoop big data tools through seamless integration with AWS tools. Use Glue and Glue Data Catalog to efficiently detect and manage the schema and structure of raw data stores - and to then effectively integrate that data into other AWS tools. Know how to clean and prepare large - and often moving - data

Collecting and storing big data
Make sure your candidate knows how to manage S3-based data and data streams using Kinesis, Redshift (including Redshift Spectrum), and Data Pipeline.

Analyzing data
Run SQL queries against big data stores in multiple states using Athena or Amazon’s implementations of Elasticsearch.

Present your analysis visually using Amazon QuickSight dashboards or deeply integrated AWS implementations of Jupyter Notebooks.

Hecho por uno de los expertos líderes

David Clinton

Pluralsight Author
Book Author

I love teaching people through my courses and books.
But it's great to design a test that, instead of assuming your ignorance, measures your success.

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