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Unlock the full power of AWS with Tiger’s unique expertise
Unlock the full power of AWS with Tiger’s unique expertise
This, coupled with a multi-cloud environment backed by customizable and adaptable open-source systems, helps organizations address their unique needs and take timely, data-driven decisions.
Expedite your transformation journey through a global computing infrastructure powered by Tiger Analytics’ expertise in AWS migration and optimization. We help you accelerate transformation and innovation effortlessly with a diverse array of tools from Amazon Web Services.
Automate a large part of your effort to ingest data and streamline pipelines with Tiger Analytics’ expertise in AWS Data Migration Service, AWS Transfer Family, AWS Glue, AWS Lambda, Amazon Kinesis Data Streaming, and AWS Data Pipeline.
We help you optimize, organize, and configure access to your data with our expertise in Amazon Simple Storage Service, AWS Lake Formation, Amazon Dynamo DB, Amazon Redshift, and Amazon RDS.
Add security and speed to your data processing with Tiger Analytics’ expertise in AWS EMR, AWS Glue, Amazon Athena, and Amazon EC2.
Prepare and visualize your data with ML modeling for better insights. We help you do this with our expertise in Amazon QuickSight, Amazon SageMaker, AWS IoT Greengrass, and Amazon Elastic Container Service.
Gain the insights you need in near real-time with our expertise in AWS Glue, Amazon EMR, Amazon Athena, and Amazon Kinesis Data Analytics.
Let Tiger Analytics help you enable fine-grained access control, security, and compliance management with our expertise in AWS Glue Data Catalog, AWS IAM, AWS IAM Identity Center, Amazon CloudWatch, AWS Key Management Services, Amazon Guard Duty, and Amazon Mice.
Fully automate your CI/CD deployment pipeline while keeping it flexible with Tiger Analytics’ expertise in AWS CodePipeline, AWS CodeDeploy, AWS CodeBuild, and AWS CodeCommit.
With the applicationsgaining momentum, the amount of data that needs to be analyzed is growing enormously and massively every day. Many business operations are impacted by issues including less scalable systems, an inability to handle different types of structured and unstructured data, higher infrastructre and maintenance costs, etc.
Businesses now rely on data for analytics, machine learning, decision making, etc. Data is stored and analyzed using a wide range of sources, such as data lakes, data warehouses, etc. The data needs to be processed first before it is loaded into these sources.
Today’s world depends heavily on data. Making analytical decisions based on the data is a
crucial part of improving and growing the business for many organizations where data is arriving
from diverse sources and producing insightful information.
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.
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