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Big Data and Analytics in Cloud Computing

Updated: Jan 31

The author Muhammad Arslan Hayat of the article:"Big Data Adaptation and Analytics in Cloud Computing".

Publication date: 16.10.2023

Today’s digital age with the exponential growth of data, traditional data processing tools are insufficient. The emergence of cloud computing offers the infrastructure to manage and analyze big data in a cost effective and efficient manner. This is because it opens the door for Advance analytical methodologies. Therefore, Big data and analytics have become a critical business strategy for many data analytics companies.

Is Big Data a Challenge?

Big data includes vast amounts of structured and unstructured data generated from various sectors which includes business, healthcare, education etc.. Analyzing these data can result in several challenges which may include data storage, processing power, scalability, and cost-effectiveness. For example, traditional on-premises infrastructure often struggles to address these challenges, which is where cloud computing comes into play.

Why choose Cloud Computing?

Cloud computing offers scalable and flexible resources

Cloud computing offers scalable and flexible resources that can adapt to the dynamic nature of big data. In particular, it delivers organizations computing services such as servers, databases, storage, networking, software and analytics. What’s more, Cloud providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud offer a range of services for big data analytics.

Big Data Adaptation in Cloud Computing

Cloud providers offer a scalable storage which allows organizations to store a wide range of data securely. Cloud services have on-demand access to computing resources which include serverless computing and virtual machines. These are essential for analyzing and processing large datasets.

For instance, ETL (Extract, Transform, Load) is about taking the data from a data source and loading it into analytical databases. This happens by applying the transformation or simplifying the process of ingesting data from various sources.

Extract, Transform, Load

Cloud Computing and Data Analytics

When the data is stored and processed in the cloud then the organizations can leverage various analytical tools and frameworks to extract valuable insights. Dashboards and reports for exploring data patterns including trends can be created by Cloud based data visualization tools.

For predictive data analytics, cloud platforms offer AI tools and machine learning services. Whereas organizations pay only for the resources they consume because of different price models offered by cloud providers.

Benefits of Big Data Adaptation and Analytics in Cloud Computing:

● Cloud computing reduces capital expenditures. It also allows organizations to pay only for resources they use.

● Cloud-based analytics tools helps organizations to make quick decisions and fast data processing

● Cloud providers invest in security measures due to which a secured platform is provided to their clients.

● Big data can be used to develop new products and improve productivity which can lead to more innovation.

Big data is increasing at a fast pace, so cloud computing is essential for organizations. Cloud Computing is considered as the best solution for storing, processing and analyzing big data. This is because of its scalable infrastructure and wide range of analytical tools. So, Cloud services largely exist because of Big Data. Neither would have existed without each other.


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