Birsa Institute of Technology (T)

Cloud computing and big data are two rapidly evolving fields in the realm of technology and data management. Cloud computing refers to the delivery of computing resources, including servers, storage, databases, networking, software, and analytics, over the internet. It allows organizations to access and utilize scalable and flexible computing infrastructure without the need for on-site hardware and software. On the other hand, big data refers to the large volumes of structured and unstructured data that organizations generate and collect. It involves the storage, processing, and analysis of massive datasets to extract valuable insights and support decision-making.

The employment prospects in cloud computing and big data are highly promising due to the increasing adoption of these technologies by organizations worldwide. Here are some potential employment prospects:

Cloud Architect: Cloud architects design and oversee the implementation of cloud computing solutions. They assess business requirements, choose appropriate cloud services, design scalable and secure cloud infrastructure, and ensure optimal performance. Cloud architects need a strong understanding of cloud platforms, virtualization, networking, and security.
Cloud Developer: Cloud developers create applications and services that run on cloud platforms. They develop and deploy cloud-based solutions, utilize cloud APIs, and integrate different cloud services. Cloud developers require proficiency in programming languages, cloud platforms, and software development methodologies.
Data Engineer: Data engineers manage and optimize the storage, processing, and integration of big data. They build data pipelines, design data architectures, and ensure data quality and reliability. Data engineers need expertise in big data technologies, data integration tools, database systems, and programming languages.
Data Scientist: Data scientists analyze large datasets to extract insights, build predictive models, and develop data-driven solutions. They employ statistical techniques, machine learning algorithms, and data visualization tools to uncover patterns and trends. Data scientists should have skills in statistical analysis, programming, machine learning, and data manipulation.
Big Data Architect: Big data architects design and implement systems to handle large volumes of data. They define data architectures, select appropriate big data technologies, and ensure scalability and performance. Big data architects need a deep understanding of big data frameworks, distributed computing, and data storage technologies.
Data Analyst: Data analysts examine and interpret data to identify trends, patterns, and actionable insights. They perform data cleansing, data mining, and statistical analysis to support decision-making. Data analysts should be proficient in data manipulation, data visualization, and data analysis tools.

The scope of cloud computing and big data is vast and expanding as organizations across industries increasingly rely on these technologies. Here are some key aspects of their scope:

Cloud Computing: Cloud computing offers a wide range of services, including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It provides scalability, cost-effectiveness, and accessibility for businesses of all sizes. Cloud computing is utilized for deploying applications, storing and processing data, running virtual machines, managing databases, and implementing artificial intelligence and machine learning algorithms. The scope extends to areas such as cloud architecture, cloud security, cloud migration, and cloud optimization.
Big Data: Big data encompasses the collection, storage, processing, and analysis of large and complex datasets. It involves handling structured and unstructured data from various sources, such as social media, sensors, transactions, and more. Organizations leverage big data to gain insights, identify patterns, make data-driven decisions, improve operational efficiency, enhance customer experiences, and drive innovation. The scope of big data includes data management, data analytics, data visualization, machine learning, and predictive modeling.

3 Years Diploma	30 Seats	At least 35% aggregate in 10th / Matric.
Lateral Entry to 3rd Semester	12 Seats	12th Pass in Science (with Math) OR 10th + (2 years ITI) OR 12th Science with Vocational / Technical.

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CLOUD COMPUTING & BIG DATA