5 Data Lake Courses to Facilitate Enterprise Data Centralization

Data lakes provide a unified storage solution for large volumes of structured, semi-structured, and unstructured data from diverse sources and, thus are essential for enterprise data centralization. Unlike traditional systems, data lakes allow organizations to store raw, unmodified data without needing immediate transformation, applying the schema only when the data is retrieved (schema on read). This flexibility supports advanced analytics, artificial intelligence, and machine learning initiatives, enabling businesses to make data-driven decisions, break down silos, and improve performance.  

For professionals seeking to master data lake concepts, online courses offer a convenient way to build expertise. These data lake courses cover designing data lake architectures, implementing data ingestion, and applying analytics using popular platforms like AWS, Azure, and Google Cloud. These courses will enable them to be well-equipped to handle the growing demands of enterprise data centralization.

Top Data Lake Courses

1. Modernizing Data Lakes and Data Warehouses with Google Cloud
2. Large-Scale Data Processing with Azure Data Lake Storage Gen2
3. Learn Spark & Data Lakes
4. Implement Data Auditing with Azure Data Lake
5. Building Data Lakes on AWS

Modernizing Data Lakes and Data Warehouses with Google Cloud

Modernizing Data Lakes and Data Warehouses with Google Cloud is the first course of the Data Engineering on Google Cloud series. It introduces the concepts of data lakes and data warehouses, explaining their differences and how they fit into modern data pipelines. Students will explore specific use cases for each type of storage and learn about the solutions offered by Google Cloud for implementing data lakes and data warehouses. The course also discusses the role of a data engineer and highlights how effective data pipelines can benefit business operations.

Additionally, the course examines the advantages of performing data engineering tasks in a cloud environment, emphasizing scalability and efficiency. 

Course Name	Modernizing Data Lakes and Data Warehouses with Google Cloud
Duration	8 hours
Provider	Coursera
Course Fee	Subscription-based - Rs. 4,117/month
Trainer	Google Cloud Training
Skills Gained	Data Lakes, Data Warehouses, Google Cloud
Students Enrolled	54,000+
Total Reviews	4.7/5 (2800+ reviews)

Large-Scale Data Processing with Azure Data Lake Storage Gen2 

Large-Scale Data Processing with Azure Data Lake Storage Gen2 by Microsoft introduces Azure Data Lake Storage Gen2 and explains its role in processing large-scale data. Students will learn how to set up and use Azure Data Lake Storage for Big Data analytics and understand how it integrates into common data processing architectures. The course also covers methods for uploading data to the storage system, enabling seamless data management. The course also teaches the robust security features available in Azure Data Lake Storage Gen2 to protect stored data. 

Course Name	Large-Scale Data Processing with Azure Data Lake Storage Gen2
Duration	2 hours
Provider	Microsoft
Course Fee	Free
Skills Gained	Networking, Security, Data Processing, Microsoft Azure, Big Data

Learn Spark & Data Lakes 

Learn Spark & Data Lakes course will help you understand the fundamentals of the big data ecosystem, data lakes and lakehouses, Spark architecture, its role in big data, and the specific challenges it addresses. You will learn to work with large datasets using Apache Spark and get an overview of how Spark processes and transforms data through distributed computing. 

Students will also use Spark for data wrangling, filtering, and transformation using PySpark and Spark SQL. They will also leverage AWS to manage data lakes effectively and work with AWS tools like S3 and AWS Glue. The course culminates in a hands-on project which includes working with sensor data to train a machine learning model. 

Course Name	Learn Spark & Data Lakes
Duration	2 weeks
Provider	Udacity
Course Fee	All Access monthly - Rs. 20,500/month
Trainer	Sean Murdock - Professor at Brigham Young University Idaho
Skills Gained	Apache Spark, AWS data lakes, ELT, Big data fluency, Data wrangling, Data Lakehouse Architecture, Data format fundamentals, etc.
Rating	4.6/5 (36,400+ ratings)
Students Enrolled	184,000+

Implement Data Auditing with Azure Data Lake 

Implement Data Auditing with Azure Data Lake course focuses on implementing data auditing, data masking, and encryption strategies for data stored in Azure Data Lake. Students will learn to secure data at rest and in transit using the Azure Cloud Portal. The course also covers planning secure endpoints, data retention strategies, and archiving to ensure effective data governance.

Major topics covered in the course include:

• Designing security for source data access.
• Applying encryption and data masking.
• Managing policies and standards for data security.

Learners will also explore how to authenticate service principles for integrating Azure Data Lake with Azure Databricks. By the end of the course, students will understand the importance of data masking, encryption policies, and key management in creating a policy-driven data lake architecture.

Course Name	Implement Data Auditing with Azure Data Lake
Duration	34 minutes
Provider	Pluralsight
Course Fee	Rs. 749 per month after 10-day trial
Trainer	Tapan Ghatalia, Pluralsight Author with 10+ years of work experience in Business Intelligence, Product Management and Cloud Architecture.
Skills Gained	Data Auditing, Data Masking, Encrypting Data, Data Retention, Data Archiving

Building Data Lakes on AWS

Building Data Lakes on AWS course by Coursera is a part of AWS Cloud Solutions Architect Professional Certificate. It is a foundational course covering the basics of AWS data lakes. The course is suitable for learners with elementary knowledge about the storage of data and its processing but have no experience in AWS data lakes. The learning begins with a definition of a data lake and continues on to ingestion of data, cataloging, preparation, and AWS Lake Formation. The students will work in a hands-on lab where they will be guided to build their data lake.

The course further covers data processing and analytics using AWS Glue; it shows how a data lake can be created using Lake Formation blueprints with automation. It concludes with modern data architectures on AWS, including a lab on publishing and consuming data products as services. The course will enable students to understand how to plan, design, and secure a data lake while effectively managing data ingestion, storage, and transformation.

Course Name	Building Data Lakes on AWS
Duration	11 hours
Provider	Coursera
Course Fee	Subscription-based - Rs. 4,117/month (Audit for free)
Trainer	Rafael Lopes, Alex G. - Amazon Web Services
Skills Gained	Machine learning, Data lake architecture, Data Analytics, Data Governance, AWS, Data Engineering
Students Enrolled	30,800+
Total Reviews	4.8/5