Cloud & Data Management

Introduction

In the era of massive digital transformation, the disciplines of Cloud & Data Management are no longer optional—they’re essential. Imagine a library: in the old days you’d build a massive archive room (on-prem infrastructure) and manually sort every book (data) by hand. Now, using cloud services you get an elastic warehouse (cloud infrastructure) and smart catalogue systems that automatically organise and deliver what you need when you need it. That’s what cloud & data management enables for modern businesses. This course on Cloud & Data Management equips you with the skills to handle both the infrastructure layer (cloud) and the information layer (data) together—with seamless integration.

By focusing on cloud architecture and data workflows, you gain the ability to design systems that store, process, secure and derive insights from huge volumes of data in a cloud environment. Whether it’s migrating legacy databases to the cloud, building data lakes, implementing data governance, or leveraging analytics platforms—all these fall under the umbrella of cloud & data management. With organisations collecting more data than ever and expecting real-time insights, specialists who can manage cloud infrastructure plus data lifecycle are in high demand. For professionals in Mumbai’s bustling tech ecosystem, this means robust career prospects: roles that blend cloud engineering, data engineering, data operations and analytics are emerging rapidly. This Cloud & Data Management course is ideal if you want to master the full stack—from cloud setup and orchestration to data ingestion, processing, storage, governance and analytics—putting you at a sweet intersection of two of the most in-demand disciplines in IT.

Course Purpose & Fit

Purpose / Goals:

• Equip students to deploy cloud infrastructure and manage enterprise-scale data ecosystems.
• Enable learners to ingest, store, process, secure and analyse data in a cloud environment.
• Prepare participants for roles that blend cloud architecture, data engineering and data management operations.
• Provide a portfolio of real-world projects: data migration, building data-lakes, analytics pipelines and cost-efficient cloud data infrastructure.

Who Should Enrol:

• Beginners with interest in cloud or data who want to build dual skills.
• IT professionals looking to expand into data engineering or cloud roles from infrastructure/operations.
• Data analysts or BI developers who want to work in cloud-native data platforms and manage data pipelines.
• Career switchers aiming for high-growth roles combining cloud and data management.

Why Take This Course:

• Unique benefits: integrated curriculum covering both cloud architecture and data lifecycle, not just one or the other.
• Industry use-cases: migrating enterprise data-warehouses to cloud, setting up data-lakes for real-time analytics, implementing governance and compliance in regulated industries.
• Tools covered: Cloud platforms (AWS/Azure/GCP basics), data services (Redshift, Azure Synapse, BigQuery), data-lake architectures, ETL/ELT pipelines, data governance frameworks, data visualisation.
• Certification prep: content mapped to cloud/data certifications (e.g., AWS Big Data Specialty, Azure Data Engineer, Google Cloud Data Engineer).
• Portfolio outcomes: build data-lake from scratch, implement streaming analytics pipeline, demonstrate cost and security optimisation.