In one sentence, data engineering is the management of systems to make data usable. --- Full article on my blog: https://cedricgaudissart.hashnode.dev/understanding-what-is-data-engineering-a-comprehensive-guide

1. What is Data
Engineering?
by Cédric Gaudissart
In one sentence, data engineering is the management of
systems to make data usable. The lifecycle of data
engineering encompasses a series of stages aimed at
transforming raw data into usable data.

2. From Data Collection
to Processing
Data Collection
Data engineers gather data from various
sources, including internal databases, IoT
devices, and external APIs. This stage is
essential for accumulating the raw materials
necessary for analysis.
Data Ingestion
This involves the transfer of data to systems
for processing and storage, often automated
by data engineers. This stage must be efficient
to handle the volume and velocity of incoming
data.
Data Processing
Data engineers validate, cleanse, and
transform data to ensure quality and usability.
This includes removing duplicates, correcting
errors, and transforming data into a consistent
format.

3. Integrating and Storing Data
Data Integration
Data engineers combine data
from disparate sources,
enriching and contextualizing
information to provide a holistic
view.
Data Storage
Data engineers organize and
store data in a scalable, secure
manner, ready for access and
analysis. Databases, data lakes,
and data warehouses are key
components.
Data Orchestration
Data engineers streamline the
coordination between different
stages, automating the data
flow through pipelines and
ensuring that data moves
seamlessly from collection to
analysis.

4. Ensuring Data Quality and Reliability
Data Quality Control
Data engineers maintain
the data's reliability and
integrity through
continuous monitoring,
validation, and correction
processes. This ensures the
data's overall quality for
informed decision-making.
Data Pipeline
Maintenance
Data engineers
continuously update,
optimize, and secure the
data processes and
technologies, ensuring an
efficient and compliant
data flow.
Data Archiving
Data engineers provide a
secure repository for
historical data, facilitating
compliance and future
accessibility while
optimizing current system
performance.

5. Data Management
Throughout the data engineering lifecycle, stringent
data management practices are upheld to ensure data
quality, privacy, and governance, underscoring the
lifecycle of data engineering as a cornerstone for data-
driven organizations.