Quantexa Data Engineer Academy (DEA) - Release 2

Summary:

The Quantexa Data Engineer Academy is an in-depth program aimed to teach Data Engineers how to build Quantexa Platforms.

An environment is provided to every user where they build a ‘mini-proof of concept’ Quantexa Platform.

Their work is then assessed by a Quantexa Academy Team Lead and a Quantexa Technical Specialist.  

With Release 2, the Data Engineer Academy now offers two pathways: the Core ER Certification (ER‑focused) and the Core Platform Certification for learners seeking broader, end‑to‑end knowledge of the Quantexa Platform.

✔ Ideal Candidates for the Quantexa DEA program

Each of our certification programs is complex in nature and is best suited to individuals that have an associated set of prerequisite skills and experience that will support their ability to obtain the related certification.

Here’s the recommended criteria for the Data Engineer Academy.

• Hands-on development experience (Java, Scala, etc.) via system integration projects or as a data scientist.
• Experience of working on fraud, financial crime, customer insight or compliance-based projects that utilize detection or predictive models.
• Experience in the Agile development methodology.
• Experience of working on projects involving statistical approaches or detection logic.
• Familiarity with data mapping, relational data, and object orientation.
• Familiarity with data processing methods, such as ETL, parsing and handling data quality-related issues.
• Experience of working with operational environments, DevOps, restart/recovery, etc.
• Experience with Hadoop, Spark, Scala (or Java), or, less ideally, Python, Elastic (optional), RESTful APIs, JSON, and Tomcat.
• Development environment skills (code control, IDEs), understanding of such processes as unit testing, design, and documentation.

Scala and Spark Pre-requisite Assessment

A fundamental understanding of Scala and Spark is key to ensuring learners' success as a Quantexa Data Engineer.

With this being the case, there is a Scala and Spark pre-requisite assessment that has been designed to ensure that you have the necessary skills to complete the associated Academy Tasks and, consequently, to qualify as a Quantexa Certified Data Engineer. 

You can learn more about it in this article: Scala Prerequisite Assessment - CoderPad.

Core ER Program

Prerequisite Assessment: Scala and Spark
Assessment: Knowledge Check / Tasks / Project Assessment
Duration: *Dependent on how well the candidate matches the program's ideal candidate selection criteria:

• Approximately 4 weeks full-time*​
• For part-time, see Self Paced Completion Times

Max Time Allowed to Complete: 2 Months
Format: eLearning & project work
Product version: 2.8.1
Training Credit Classification: Certification

Summary:

An in-depth technical program for data engineers working with the Entity Resolution (ER) functionality of the Quantexa Platform, with a strong focus on the Data Ingestion stage.​

Users are expected to complete a series of activities and graded assessments to demonstrate their practical skills. ​

Modules include:

1. Part 1 – Introduction: Academy Overview and environment setup (VDI, IntelliJ, and Elasticsearch).
2. Part 2 – ETL 1: Importing raw data sources, understanding and configuring Parsers, building and populating the Document Data Model.
3. Part 3 – ETL 2: Extracting Entity records using Data Fusion, loading Documents and Entity Records into Elasticsearch.
4. Part 4 – Entity Resolution: Configuring and executing Batch and Dynamic ER using the Resolver, validating resolution quality.

Outcome: 

On successful completion learners will be awarded the Quantexa Data Engineer: Core ER Certification (including the associated badge and certificate).

Self Paced Completion Times

*Falls outside of standard program duration allowance plus permitted 2-month extension – not advised

Core Platform Program

Prerequisite Assessment: Scala and Spark
Assessment: Knowledge Check / Tasks / Project Assessment
Duration: *Dependent on how well the candidate matches the program's ideal candidate selection criteria:​

• Approximately 5 weeks full-time*​
• For part-time, see Self Paced Completion Times

Max Time Allowed to Complete: 4 Months
Format: eLearning & project work
Product version: 2.8.1
Training Credit Classification: Certification

Summary:

An in‑depth technical program for data engineers who want broader, end‑to‑end knowledge of the Quantexa Platform.
​
Learners complete a modular learning journey with practical activities, integrated knowledge checks and graded assessments to demonstrate their practical skills.​

Modules include:

1. Part 1 – Introduction: Academy Overview and environment setup (VDI, IntelliJ, and Elasticsearch).
2. Part 2 – ETL 1: Importing raw data sources, understanding and configuring Parsers, building and populating the Document Data Model.
3. Part 3 – ETL 2: Extracting Entity records using Data Fusion, loading Documents and Entity Records into Elasticsearch.
4. Part 4 – Entity Resolution: Configuring and executing Batch and Dynamic ER using the Resolver, validating resolution quality.
5. Part 5 – UI Configuration: Configuring the Quantexa User Interface: Search 2 setup, Viewers (Document, Entity, Search Result), Investigations (Resource Viewer, Network View), and Dynamic Expansions.
6. Part 6 – Scoring with Assess: Designing and implementing Scores at Document and Entity level, configuring Scorecard; executing Scores in Batch and Dynamic modes; validation (unit tests, checkpoints, Scorecard and UI validation).

Outcome: 

On successful completion learners will be awarded the Quantexa Data Engineer: Core Platform Certification (including the associated badge and certificate).

Self Paced Completion Times

*Falls outside of standard program duration allowance plus permitted 2-month extension – not advised​