The Basics of Data Engineering with IABAC

Basics of
Data Engineering
with IABAC

Content
Data Engineering Fundamentals
Role of a Data Engineer
Data Engineering Lifecycle
Data Engineering Tools
Cloud Platforms for Data Engineering
Best Practices in Data Engineering
Career Paths in Data Engineering
IABAC and Data Engineering Certification
Thank You
www.iabac.org

01 02 03
Definition Processes Importance
Data engineering involves the
collection, organization, and
processing of data to make it
accessible, usable, and
meaningful. In simple terms, it
focuses on creating data
collection, storage,
transformation, and analysis
processes for large amounts
of raw and structured data.
Data engineering
encompasses the set of
all processes that collect
and integrate raw data
from various resources
into a unified and
accessible format.
It is the discipline that
designs, builds, and
maintains the systems
and infrastructure for
collecting, storing, and
analyzing data.
Data Engineering Fundamentals
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Role of a Data Engineer
Responsibilities Skills Required Training and Resources
Data engineers allow an
organization to efficiently and
effectively collect data from
various sources, generally storing
that data into a data warehouse or
data lake.
The basics of Linux, database
management, servers, scripting
(bash/Powershell/Python), and
even some back end/server-side
language are essential for a data
engineer.
There are various courses and
resources available for beginners
to learn about databases, Docker,
and analytical engineering.
www.iabac.org

Data Engineering Lifecycle
Lifecycle Overview
Importance of Lifecycle
Resource Recommendation
The data engineering lifecycle involves data generation, storage,
ingestion, transformation, and serving, making it a vital field in the
tech industry.
Understanding the data engineering lifecycle is crucial for designing
and building systems for collecting, storing, and analyzing data at
scale.
The book 'Fundamentals of Data Engineering: Robust Systems'
provides a comprehensive guide to the data engineering lifecycle.
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01 02 03
Data Engineering Tools
Database
Management
Data Warehousing ETL Tools
Understanding database
systems and tools is
crucial for data engineers
to efficiently manage and
manipulate data.
Data engineers work with
data warehousing tools to
store and manage large
volumes of data for
analysis and reporting.
Extract, Transform, Load
(ETL) tools are essential
for data engineers to
integrate data from
various sources into a
unified format.
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Cloud Platforms for Data Engineering
Cloud Services Big Data Technologies Serverless Computing
Data engineering often involves
working with cloud platforms such
as AWS, Azure, and Google Cloud
for scalable and cost-effective
data processing.
Understanding big data
technologies like Hadoop, Spark,
and Kafka is essential for data
engineers to handle large
datasets.
Knowledge of serverless
computing platforms like AWS
Lambda and Azure Functions can
streamline data engineering
processes.
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01 02 03
Best Practices in Data Engineering
Data Quality
Management
Scalability and
Performance
Security and
Compliance
Ensuring data quality
through validation,
cleansing, and monitoring
is a critical best practice in
data engineering.
Designing systems for
scalability and
performance optimization
is essential for handling
large volumes of data.
Implementing robust
security measures and
ensuring compliance with
data regulations are vital
best practices.
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Career Paths in Data Engineering
Data Engineering Roles Industry Demand Career Growth
Data engineers can pursue roles
such as Data Analyst, Data
Scientist, Database Administrator,
or Data Architect.
The demand for data engineers is
high across various industries,
including technology, finance,
healthcare, and e-commerce.
Data engineering offers
opportunities for career growth,
with roles ranging from entry-level
positions to senior leadership
roles.
www.iabac.org

IABAC and Data Engineering Certification
About IABAC
Certification Benefits
Student Resources
The International Association of Business Analytics Certifications (IABAC) offers globally recognized certifications in data
engineering.
IABAC certifications validate expertise in data engineering and enhance career prospects for students and professionals.
IABAC provides comprehensive resources and training materials to prepare for data engineering certification exams.
www.iabac.org

The Basics of Data Engineering with IABAC

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