With Amazon EMR, multiple data stores can be leverage like Amazon S3, HDF), and Amazon DynamoDB
Enterprises today have a large volume of data being produced and collected across various digital touch points. To maximize the value and deliver insights from this large volume of data, there is a need for a solution that can process and deliver interactive analytics and machine learning.
Amazon EMR is the leading cloud big data solution for processing vast amounts of data, delivering interactive analytics, and machine learning using open-source frameworks such as Apache Spark, Apache Hive, and Presto. Amazon EMR is a managed cluster platform that simplifies running big data frameworks on AWS to process and analyze large volumes of data.
With more than 100+ certified AWS experts, Tiger Analytics has successfully implemented Amazon EMR and other AWS services for multiple customers across various industries.
Enterprises today have a large volume of data being produced and collected across various digital touch points. To maximize the value and deliver insights from this large volume of data, there is a need for a solution that can process and deliver interactive analytics and machine learning.
Amazon EMR is the leading cloud big data solution for processing vast amounts of data, delivering interactive analytics, and machine learning using open-source frameworks such as Apache Spark, Apache Hive, and Presto. Amazon EMR is a managed cluster platform that simplifies running big data frameworks on AWS to process and analyze large volumes of data.
With more than 100+ certified AWS experts, Tiger Analytics has successfully implemented Amazon EMR and other AWS services for multiple customers across various industries.
Large-scale distributed data processing jobs, interactive SQL queries, and machine learning applications
Extraction of data from various sources and data processing
Real-time analysis to create long-running, highly available, streaming data pipelines.
Supports open- source ML frameworks such as Apache Spark MLlib, TensorFlow, and Apache MXNet.
Provides end to end capability right from Data Ingestion, Data Quality and transformation capabilities required for a Data Lake. Accelerates data movement from source systems into Amazon EMR thereby enabling quick onboarding of analytics and ML use cases.
Open-Source framework for Data Quality. It is highly configurable with table & field level rules, integrated with Airflow and monitoring tools.
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