Kinesis / Real-Time Data Analyses - Professional Services
Kinesis / Real-Time Data Analyses Professional Services As Customers started their Big Data Journey by applying advanced analytics on sheer amount of data and build their new Data Lakes, they focus on enhancing their existing DWH/BI platforms by introducing AWS Products like EMR, Kinesis, Redshift and more. AWS Big Data Professional Services will offer a set of services to our customers that will focus on both strategy and technology implementation utilizing AWS Kinesis.
Key Activities Kickoff call Scoping Big Data Analytics Project Bootcamps/Workshops Presentation of Results Define Roadmap for Guidance Kinesis Guidance Partner ISV and SI Support
Benefits
Gain well defined Big Data Infrastructure and AWS Kinesis setup. Deliver value in short time engagement. Utilize AWS Kinesis in the most efficient manner in terms of scalability and cost when harness sheer amount data. Develop Best Practice for AWS Kinesis real-time data processing.
Deliverables*
Boot Camp Workshops (3-5 days) Work on Real Use Case with real data on customer site. Assist customers to gain Hands-on experience working on AWS Kinesis. Guidance with best practices on design and implementation efforts based on industry trends and patterns for real-time data analyses and AWS Kinesis. Design Principles and Guidance (4-8 weeks) Focus on real time data processing and integration with services such as AWS Kinesis and Spark. Create reusable repositories containing reference architecture and code samples. Providing best practices for Integration with other AWS services such as AWS EMR, Redshift, S3, DynamoDB. Provide training sessions and programs on implementing real-time data analyses solutions using AWS Kinesis, Spark and Storm. Ongoing Design Oversight and Direction (5-10 days) Best practice guidelines for AWS Kinesis design, management and performance considerations. Assistance in defining any metrics that may be required for the testing and benchmarking exercise.
Target Audience DWH/BI Directors, Data Engineer groups, Data Science Team, Business Analysts
Roles and Responsibilities
AWS Professional Services: Leads discovery workshop, planning & deliverables Customer Project Manager: Coordinates customer contributors and logistics To learn more, contact your Amazon Web Services Account Manager
* Number of days is estimated, and may vary by environment size and other organization-specific details. June 1, 2014
Review and Future Directions
Requirements Big Data Stakeholders Data Science Team Chief Data Officer Relevant Business units Data Engineering Team
Related Packages BDA – Big Data Workshop BDA – EMR Architecture BDA – Redshift Architecture BDA – Big Data Acceleration BDA – Big Data POC
Key Activities Kickoff call Scoping Big Data Analytics Project Bootcamps/Workshops Presentation of Results Define Roadmap for Guidance Kinesis Guidance Partner ISV and SI Support
Benefits
Gain well defined Big Data Infrastructure and AWS Kinesis setup. Deliver value in short time engagement. Utilize AWS Kinesis in the most efficient manner in terms of scalability and cost when harness sheer amount data. Develop Best Practice for AWS Kinesis real-time data processing.
Deliverables*
Boot Camp Workshops (3-5 days) Work on Real Use Case with real data on customer site. Assist customers to gain Hands-on experience working on AWS Kinesis. Guidance with best practices on design and implementation efforts based on industry trends and patterns for real-time data analyses and AWS Kinesis. Design Principles and Guidance (4-8 weeks) Focus on real time data processing and integration with services such as AWS Kinesis and Spark. Create reusable repositories containing reference architecture and code samples. Providing best practices for Integration with other AWS services such as AWS EMR, Redshift, S3, DynamoDB. Provide training sessions and programs on implementing real-time data analyses solutions using AWS Kinesis, Spark and Storm. Ongoing Design Oversight and Direction (5-10 days) Best practice guidelines for AWS Kinesis design, management and performance considerations. Assistance in defining any metrics that may be required for the testing and benchmarking exercise.
Target Audience DWH/BI Directors, Data Engineer groups, Data Science Team, Business Analysts
Roles and Responsibilities
AWS Professional Services: Leads discovery workshop, planning & deliverables Customer Project Manager: Coordinates customer contributors and logistics To learn more, contact your Amazon Web Services Account Manager
* Number of days is estimated, and may vary by environment size and other organization-specific details. June 1, 2014
Review and Future Directions
Requirements Big Data Stakeholders Data Science Team Chief Data Officer Relevant Business units Data Engineering Team
Related Packages BDA – Big Data Workshop BDA – EMR Architecture BDA – Redshift Architecture BDA – Big Data Acceleration BDA – Big Data POC
