Global Certificate in AWS & Azure: Data Lakes and Analytics

Name: Global Certificate in AWS & Azure: Data Lakes and Analytics
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The Global Certificate in AWS & Azure: Data Lakes and Analytics is a comprehensive course designed to equip learners with essential skills for managing and analyzing big data using Amazon Web Services (AWS) and Microsoft Azure. This certification course emphasizes the importance of data lakes, a centralized repository for storing and analyzing large volumes of structured and unstructured data, and analytics, the process of examining data to draw meaningful insights.

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AboutThisCourse

With the exponential growth of data and the increasing demand for data-driven decision-making, there is a high industry demand for professionals who can manage and analyze big data effectively. This course provides hands-on experience with AWS and Azure data lake services, enabling learners to acquire the skills necessary to design, implement, and manage data lake solutions in real-world scenarios. Upon completion, learners will be equipped with essential skills for career advancement, including the ability to design and implement data lake solutions using AWS and Azure, perform big data analytics using SQL and Hive, and optimize data lake performance and security. This certification course is an excellent opportunity for professionals looking to enhance their skillset and stay competitive in today's data-driven economy.

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Here are the essential units for Global Certificate in AWS & Azure: Data Lakes and Analytics:

• Fundamentals of Data Lakes: Understanding the concept, components, and benefits of data lakes in modern data analytics. Includes topics such as data ingestion, storage, processing, and security.

• AWS Data Lake Services: Explores AWS-specific data lake services such as Amazon S3, Amazon Kinesis, AWS Glue, and Amazon Redshift. Covers how to design, build, and manage data lakes in the AWS ecosystem.

• Azure Data Lake Services: Covers Azure-specific data lake services such as Azure Data Lake Storage, Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. Includes hands-on experience with building and managing data lakes in Azure.

• Big Data Processing with Hadoop and Spark: Covers big data processing frameworks such as Hadoop and Spark. Includes hands-on experience with setting up and using these frameworks for data processing and analytics.

• Data Analytics with SQL and NoSQL: Explores the use of SQL and NoSQL databases for data analytics. Covers topics such as data warehousing, data modeling, and query optimization.

• Machine Learning with AWS and Azure: Covers machine learning techniques and algorithms for data analytics. Includes hands-on experience with using AWS and Azure-specific machine learning services such as Amazon SageMaker and Azure Machine Learning.

• Data Visualization and Reporting: Covers best practices for data visualization and reporting. Includes hands-on experience with using tools such as Power BI, Tableau, and AWS QuickSight for creating interactive reports and dashboards.

• Security and Compliance for Data Lakes: Covers

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EntryRequirements

BasicUnderstandingSubject
ProficiencyEnglish
ComputerInternetAccess
BasicComputerSkills
DedicationCompleteCourse

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FastTrack GBP £140

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AcceleratedLearningPath

ThreeFourHoursPerWeek
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StandardMode GBP £90

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TwoThreeHoursPerWeek
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GLOBAL CERTIFICATE IN AWS & AZURE: DATA LAKES AND ANALYTICS

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London School of International Business (LSIB)

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05 May 2025

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