Benefits of Big Data Processing With Amazon EMR

AWS's big data processing comes with a treasure trove of benefits. Here are some primary advantages of the Amazon EMR migration
Cost Savings
When you, as a business, do not have to bear the cost of heavy hardware, physical facilities, and other utilities, you save big. Typically, integrating the EMR data migration for your big data processing needs will cost you around 40% less. 
Increased Flexibility
With flexible resource provisioning available, AWS EMR migration allows you to scale up or scale down, considering your business needs and preferences. This streamlines the management to a granular level.
Smooth Deployment
The EC2 instances in your EMR execute the work that you submit to the cluster. To deploy, choose the instance size and type the preferences that best meet your cluster's processing requirements, and you're done. It's that simple.
Higher Reliability
The EMR-driven AWS big data processing can automatically eliminate and replace the instances that occur as failures by constantly monitoring notes. You also get complete control over your cluster, making the AWS system a go-to choice for big data.
Increased Security
With many highly encrypted AWS services, including IAM and Amazon VPC, Amazon EMR delivers the most secure data clusters that you can expect. Don’t wait any longer. Sign up for Agilisium’s robust EMR migration.
End-to-end Solution
From access management to robust data pipelines, big data optimization lets you do it all with ease. Discover, batch, and protect data all in one place with Amazon EMR S3 data lakes. 

Top Use Cases

Perform Real-time Data Analytics 
Analyze real-time data from Amazon Kinesis, Apache Kafka, or other data streams with Apache Spark Streaming on the Amazon EMR platform. Create highly-available, fault-tolerant, and long-running streaming data pipelines.
Create Scalable Data Pipelines 
Extract and process your data from a plethora of data sources using scalable pipelines - and make real-time data access available for your users and applications. 
Personalize Digital Ads
Leverage the clickstream analysis feature of Amazon EMR to segment users accurately, understand their affinity and deliver more effective and personalized digital ads.  
Generate Valuable Insights Using Log Analysis 
Extract valuable business insights from unstructured (or semi-structured) data (generated by web and mobile applications) by performing log analysis.
Accelerate ML Adoption
Leverage EMR's built-in machine learning (ML) capabilities for the Hadoop framework to create decision-making algorithms – based on decision trees, random forests, support vector machines, and logistic regression.
Analyze Genomics data
Among the significant use cases in the medicine and telecommunications industry domains, processing and analyzing enormous genomic data volumes to churn out hidden insights quickly and efficiently.

How It Works

Our Offers


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Our Case Studies

Agilisium is the fastest-growing Cloud Transformation & Data Analytics company with strong expertise in Data lake solutions, Data Warehouse Engineering, Data Migration & Modernization.

Built A Unified Tableau Dashboard Migrated From DOMO

Learn how we Re-engineered & Migrated DOMO dashboards to Tableau in Snowflake, reducing 80% of Compute Time & 45% of TCO
Read Case Study

Improved the Retention Rate by 70% by delivering Personalized user recommendations for an American mass media house conglomerate

Viewership details of each user are captured from various partners such as Hulu, Youtube, AppleTV, etc. and stored in Redshift
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How a F500 Pharmaceutical Commercial Team achieved Data Democratization and reduced Drug Commercialization Cost by 30%

Agilisium used AWS services to rearchitect a commercial data lake and a data warehouse with end-to-end process automation
Read Case Study


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How to get started?

AWS’ Migration Acceleration Program (MAP) is a comprehensive cloud-migration program designed to accelerate your cloud migration and modernization efforts with minimal costs. AWS’ MAP outcome-driven methodology has been honed over thousands of enterprise migrations and created by AWS to reduce costs and break down the complexities of enterprise migrations.
Leverage the Power of Big Data for Your Business Using Amazon EMR
Save costs and simplify your EC2 deployment with our end-to-end EMR solutions. Utilize our Amazon EMR expertise for a host of different use cases in your business.

Our most recent work


What is AWS Big Data Processing?

AWS Big Data is the collection, storage, and utilization of Big Data on the AWS platform. AWS Big Data processing includes a range of supported capabilities like data analytics and scalable data storage.

What is Amazon EMR and what is used for?

Amazon EMR (short for Elastic MapReduce) is a cloud-based managed cluster platform that simplifies the execution of Big Data frameworks including Apache Spark and Hadoop on the AWS. It is used for AWS Big Data processing and analysis.

What are the benefits of AWS Big Data processing?

For Big Data analytics, Amazon Web Services (AWS) provides a range of managed services that can help you build, secure, and scale Big Data applications easily and with speed. Some of its benefits include low operational costs, business agility, and improved workforce productivity.

Why should you choose AWS for big data processing?

AWS provides the complete portfolio of cloud computing services that can help you build, secure, and deploy your Big Data applications on the cloud. It does not require any on-premises hardware and infrastructure.

What AWS service is best used for big data processing?

Amazon EMR is the best service for quick Big Data processing as it saves time in the configuration, commissioning, and management of Hadoop-based clusters. Using EMR, organizations can easily build workflows and monitor their Big Data analysis.

How to process big data in AWS?

With a host of features and services, AWS enables organizations to collect, store, and process Big Data on the cloud platform.

What is the difference between Amazon Gue and EMR?

Both AWS Glue and EMR can support ETL workflows. However, there are some significant differences between the two services. The EMR is a big data processing tool, whereas the ETL helps data engineers move and alter data via Amazon S3.

Is Amazon EMR fully managed?

Yes, Amazon EMR is sophisticated, fully managed software that can be deployed with a single sign-on. It is managed via Jupyter Notebooks and leverages automated infrastructure provisioning. 

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