Free
Free access this course
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LevelAll Levels
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Total Enrolled4
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Duration1 hour 30 minutes
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Last UpdatedOctober 31, 2024
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CertificateCertificate of completion
Hi, Welcome back!
Free
Free access this course
-
LevelAll Levels
-
Total Enrolled4
-
Duration1 hour 30 minutes
-
Last UpdatedOctober 31, 2024
-
CertificateCertificate of completion
Course content:
Module 1 : Introduction to Data and Data Science
This module provides a foundational overview of data, its types, and the growing importance of data science in various industries. Learners will explore different forms of data, the evolution of data over time, and key concepts in data science, including its lifecycle, team roles, and applications.
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What is Data
01:36 -
Structured vs. Unstructured Data
01:52 -
Data Back Then and Now
01:11 -
Types of data
01:59 -
Human-Generated Data
01:24 -
Computer generated data
01:52 -
Introduction to Data Science
01:58 -
Data Science Lifecycle
04:47 -
The Data Team
00:43 -
Data Analysts
02:59 -
Data Engineers – Part1
01:15 -
Data Engineers – Part2
01:53 -
Data Scientists
02:35 -
business Analysts and BI Analysts
02:33 -
Data Science Applications and Why Data Science is Important
01:38 -
Data Jobs
01:25 -
Data Science Quiz
Module 2 : Big Data Engineering
The Big Data module explores the vast and complex landscape of data characterized by high volume, velocity, variety, veracity, and value, originating from diverse sources like social media, IoT devices, and transactional systems. It covers different data types, including structured, unstructured, and semi-structured data, and highlights applications across industries such as healthcare, finance, retail, and transportation. Key challenges include ensuring data quality, maintaining privacy, and integrating various data sources. The module also explains how Big Data works through data ingestion, storage solutions like data lakes and warehouses, processing methods, and the importance of analysis and visualization. Additionally, it compares data storage architectures, emphasizing the evolving role of data lakehouses in accommodating both structured and unstructured data needs.
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Data keep on growing
00:00 -
Define Big Data
00:00 -
Where Big Data Comes From
00:00 -
How to deal with Big Data
00:00 -
The Real Time Analytics
00:00 -
Introduction to big data
00:00 -
Types of data in big data
00:00 -
Big data characteristics
00:00 -
Big data applications
00:00 -
Big data challenges
00:00 -
How big data works
00:00 -
Data warehouse vs Data Lake vs Data lakehouse
00:00 -
ETL VS ELT
00:00 -
Solutions for Big Data Analytics
00:00 -
The network (Internet)
00:00 -
Big Data Engineering
00:00 -
Key aspects of Big Data Engineering
00:00 -
Big Data Engineer
00:00 -
Big Data Engineering Quiz
Module 3 : Data Governance
Data governance is the management of data availability, quality, integrity, and security within an organization, and companies should implement it early to ensure effective data usage, with key aspects including data quality, security, compliance, stewardship, and architecture, along with steps like defining goals, assigning roles, developing policies, implementing tools, and monitoring effectiveness.
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What is data governance
00:00 -
Complies with laws
00:00 -
GDPR and CCPA
00:00 -
When should companies start implementing data governance
00:00 -
Key aspects of data governance
00:00 -
Key Steps for Implementing an Effective Data Governance Framework
00:00 -
Step 1: Preparation and Planning
00:00 -
Step 2 : Establishing the Organizational Structure
00:00 -
Step 3 : Implementing Data Management Strategies
00:00 -
Step 4 : Tools and Technologies
00:00 -
Step 5 : Reviewing and Improving Processes
00:00 -
Step 6 : Communication and Training
00:00 -
Next
00:00 -
Data governance quiz
What you will learn:
- Understand the foundations of data, including the differences between structured and unstructured data, and how data has evolved and grown over time.
- Learn what big data is, where it comes from, its unique characteristics, and why it’s so valuable in modern industries.
- Explore data storage options, including data warehouses, data lakes, and data lakehouses, and understand when to use each for managing diverse data needs.
- Compare ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes, learning their roles in preparing data for analysis.
- Discover how real-time analytics works and examine big data applications across various sectors to see how data enables fast, data-driven decisions.
- Understand the essentials of data governance, including its key aspects, why it’s important, and steps for implementing an effective governance framework.
- Learn about data science, its lifecycle, and explore different data-related roles within a data team.
- Gain insights into big data engineering, its critical role in building scalable systems for data storage, management, and processing, and key skills for a career as a big data engineer.
- This comprehensive set of concepts will provide you with a strong understanding of data, big data, and data science, setting the foundation for future roles in the data-driven industry.
Course requirements:
- No prior experience needed; access to a computer with internet; engage in discussions, complete assignments on time, and uphold academic integrity.
This course includes:
- This course includes the following materials:
- Lecture Slides: Presentations summarizing key concepts for each module.
- Video Lectures: Recorded sessions providing in-depth explanations and discussions.
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Instructor:
Eng Mohammed
Big Data Engineer and Data Consultant @ ISD Company