| Module Title: | Data Engineering |
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| Language of Instruction: | English |
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| Teaching & Learning Strategies: |
This module is 100% delivered interactively within a laboratory setting (on online, as needed). |
| Module Aim: |
To provide an overview of modern data engineering practices, tools, and methods. |
| Learning Outcomes |
| On successful completion of this module the learner should be able to: |
| LO1 |
Clean and wrangle data from multiple sources into a usable state. |
| LO2 |
Organize the collection, processing, and storage of data from different data sources. |
| LO3 |
Design and build ETL and ELT processes and pipelines. |
| Pre-requisite learning |
Module Recommendations
This is prior learning (or a practical skill) that is recommended before enrolment in this module.
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| No recommendations listed |
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. |
| No incompatible modules listed |
Co-requisite Modules
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| No Co-requisite modules listed |
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. |
| No requirements listed |
Module Content & Assessment
| Indicative Content |
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Data Formats
Understanding internet data-types: MIME, quoted-printable, Base64 (and others). Data Sources: TXT, CSV, JSON, Web Data, APIs, ERP, CRM, Databases. Structured data, Semi-structured data, and unstructured data.
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Data Storage
SQL Databases, Document Databases, Graph Databases, Data Warehouses, Data Lakes, Dataframes.
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ETL/ELT
Extract, Transform, and Load and Extract, Load, and Transform: data cleaning, munging, parsing, converting, mining, and saving.
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Data Platforms
Big Data, Map Reduce, Cloud-scale data, distributed data processing, Data pipelines, Parallel Computation Platforms, Scaling Issues/Concerns.
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| Assessment Breakdown | % |
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| Project | 100.00% |
| Project |
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| Assessment Type |
Assessment Description |
Outcome addressed |
% of total |
Assessment Date |
| Project |
TBD |
1 |
35.00 |
n/a |
| Project |
TBD |
2 |
20.00 |
n/a |
| Project |
TBD |
3 |
45.00 |
n/a |
| No End of Module Formal Examination |
SETU Carlow Campus reserves the right to alter the nature and timings of assessment
Module Workload
| Workload: Full Time |
| Workload Type |
Frequency |
Average Weekly Learner Workload |
| Laboratory |
12 Weeks per Stage |
2.00 |
| Estimated Learner Hours |
15 Weeks per Stage |
6.73 |
| Total Hours |
125.00 |
Module Delivered In
| Discussion Note: |
First draft of one of the elective modules for final year undergrad offerings. |
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