The last decade has shown that the competitive advantage gained by a data driven enterprise is proportional to the agility and reliability of its data management practices. The ability to scale data infrastructure to match demand, to build robust data pipelines, support a variety of analytics initiatives, democratize data while still imposing good data governance — these are part of an ever-growing list of expectations of your data architecture, infrastructure, and team. The cost of failing to meet any of these expectations can have an outsized impact on a business’ performance.

Given the stakes, you cannot afford to be saddled with an outdated, inflexible data platform. A proven, cloud-based, scalable data and analytics platform — that constantly evolves to keep up with the changing analytics landscape must be a key component of your data strategy. If overnight, you are asked to support Generative AI and Large Language Models (LLMs) in your applications, you shouldn’t be hampered by what your platform can and cannot do. So where do you start with putting together such a flexible architecture that can extend your organization’s analytic capabilities in any direction that the business dictates?

Infinitive has deep experience in designing and building data solutions on the AWS cloud. Utilizing our proven Data Transformation Methodology, we will develop an architecture that best fits your strategic needs utilizing AWS services for data migration, data engineering, storage and analytics. As a long-term AWS services partner, we are proficient in all relevant AWS offerings in this space, with the hard-won experience of deploying solutions at scale across various industries. With our structured approach to migrating your data platform to AWS, we can accelerate your time to deployment, while delivering a robust, observable and maintainable implementation following data ops best practices.

The last decade has shown that the competitive advantage gained by a data driven enterprise is proportional to the agility and reliability of its data management practices. The ability to scale data infrastructure to match demand, to build robust data pipelines, support a variety of analytics initiatives, democratize data while still imposing good data governance — these are part of an ever-growing list of expectations of your data architecture, infrastructure, and team. The cost of failing to meet any of these expectations can have an outsized impact on a business’ performance.

Given the stakes, you cannot afford to be saddled with an outdated, inflexible data platform. A proven, cloud-based, scalable data and analytics platform — that constantly evolves to keep up with the changing analytics landscape must be a key component of your data strategy. If overnight, you are asked to support Generative AI and Large Language Models (LLMs) in your applications, you shouldn’t be hampered by what your platform can and cannot do. So where do you start with putting together such a flexible architecture that can extend your organization’s analytic capabilities in any direction that the business dictates?

Infinitive has deep experience in designing and building data solutions on the AWS cloud. Utilizing our proven Data Transformation Methodology, we will develop an architecture that best fits your strategic needs utilizing AWS services for data migration, data engineering, storage and analytics. As a long-term AWS services partner, we are proficient in all relevant AWS offerings in this space, with the hard-won experience of deploying solutions at scale across various industries. With our structured approach to migrating your data platform to AWS, we can accelerate your time to deployment, while delivering a robust, observable and maintainable implementation following data ops best practices.

Data Storage

Data Lakes on S3

S3 is Amazon’s object storage service. A low-cost, virtually infinitely scalable, reliable storage service, S3 offers a great option for building a data lake for storing vast amounts of data at a reasonable price point. This is an ideal solution use cases like, storage of historical data for regulatory compliance, data consolidation and staging, a repository of data sets for data science and machine learning, IOT data, log file analysis etc. The common thread in all these use cases is the need to store vast quantities of data at a low cost. Infinitive has built several data lakes for its clients with data stored in formats like columnar formats like Parquet, with appropriate partitioning schemes to ensure efficient query using AWS services like Athena and Redshift Spectrum.

Amazon RDS

RDS is a managed relational database service, a great option for organizations that are looking to migrate their on-prem databases to the AWS cloud as part of their cloud migrations. With the ability to choose one of several database engines, including Amazon’s own Aurora, appropriate network design, use of read replicas etc. we can put together a reliable, scalable, highly available transactional relational database that is the right blend of cost and performance to fit your application’s needs.

Redshift

Redshift is Amazon’s Petabyte scale MPP (Massively Parallel Processing) Data Warehouse, an ideal option for businesses seeking a cloud data warehouse that can scale with their needs. With RA3 nodes with managed storage, Redshift provides the means to scale storage and compute independently – making it possible to analyze vast amounts of data without a corresponding compute spend. With proper table design and optimizations, Redshift can serve your business’ high performance data warehousing and BI needs without incurring a correspondingly high cost as you did with legacy data warehouses. Infinite has implemented Redshift based analytics solutions for its clients, further extending it with Redshift Spectrum to analyze vast amounts of data residing in data lakes.

Purpose-built Databases

Where appropriate, a resilient data architecture makes use of purpose-built databases. Infinitive has experience building solutions using AWS services like DynamoDB (a high-performance Key-value database) and Neptune (a graph database). Infinitive, with its deep expertise in building cloud data architectures, can help you determine the appropriate use of AWS’ purpose-built database services in your data architecture to meet your objectives.

Data Transformation

Glue

AWS Glue is a serverless offering which can be used to connect to a diverse set of data sources, ingest data from them, transform, store and catalog that data. For analytics databases to be built on AWS, Glue is a natural fit as the ETL engine. Scalable, serverless with low administrative overhead, ability to build complex transformations using the python SDK, automatic orchestration of pipelines with triggers and schedules, cataloging metadata – all features useful for building reliable data analytic solutions. Infinitive uses Glue as its go-to ETL tool when building data lakes and warehouses on AWS.

EMR

EMR provides scalable distributed compute that is often used for data transformation, typically used with distributed computing frameworks like Apache Spark to perform large scale data processing tasks. As this is a fully managed service, there is little administrative overhead for managing the infrastructure, so our clients can focus more on the transformation implementation. With tight integration with other AWS services like S3, Kinesis and Redshift, EMR Is a good choice for running large scale transformations as part of AWS analytics solutions.

Data Movement

DMS

Data Migration Service (DMS) is a key component for moving data into and around the AWS cloud. Infinitive has used DMS in architectures that required moving on-prem databases to the cloud, for replication and for change data capture. This is a versatile tool that can work across multiple database engines like Oracle, SQL Server, MySQL and Aurora, potentially migrating data from one to the other

Kinesis & MSK

The Kinesis suite and MSK (Managed Streaming for Kafka) are AWS services that provide managed data streaming capabilities on the Amazon cloud. This is often a key component of data architectures that need to deal with real-time ingestion of streaming data at scale. For use cases that require real-time analytics, these components become an indispensable part of the architecture.

Query & BI Tools

QuickSight

AWS QuickSight is a fully managed BI service that is an alternative to tools like Tableau and PowerBI. This tool allows you to build and share reports and dashboards with your team, analyzing and visualizing data you have organized in your AWS data lake or warehouse. The natural language query capabilities enabled through QuickSight Q makes BI accessible to business users without specific data analytics expertise. This is a cloud scale BI solution that fits well into any AWS based data analytics architecture, with a pricing model that scales with number of users. As an Amazon QuickSight Delivery Partner, Infinitive has deep expertise in building analytics solutions based on QuickSight.

Athena & Redshift Spectrum

Athena is a serverless federated query engine. With minimum administrative overhead, and usage-based costs, Athena is a viable option querying data lakes. Redshift Spectrum serves a similar purpose and is useful in cases where data warehouse data needs to be queried alongside external data in data lakes. Both these options allow the use of standard SQL for accessing data for analytics purposes. Infinitive has utilized both Athena and Redshift in solutions in client applications, providing reliable, cost-effective means of analyzing data. 

Conclusion

With a suite of services that provide a comprehensive coverage of all components needed for data analytics – data collection, transmission, ingestion, transformation, storage and analysis – AWS provides all you need to build a data analytics solution to meet any business needs. As a long-term AWS services partner, Infinitive has built data analytics solutions for businesses, large and small, in several different industries. Leverage Infinitive’s expertise, with AWS’ complete suite of analytics offerings to build transformative analytics applications for your business.

Conclusion

With a suite of services that provide a comprehensive coverage of all components needed for data analytics – data collection, transmission, ingestion, transformation, storage and analysis – AWS provides all you need to build a data analytics solution to meet any business needs. As a long-term AWS services partner, Infinitive has built data analytics solutions for businesses, large and small, in several different industries. Leverage Infinitive’s expertise, with AWS’ complete suite of analytics offerings to build transformative analytics applications for your business.

Why Work With Infinitive

Our solutions are built on scalable, secure, low-latency, cloud-based technology, all powered by our deep experience with leading media technology vendors. We will roll up our sleeves and work alongside your teams from initial strategy and vision to design and implementation, to full user adoption. We are with you every step of the way.

  • Worked with 9/10 of the top Media companies in the world
  • Implementation experience with most of the premier Ad Technology solution providers
  • Employees that are Ad business and transformation veterans bringing best practices to your programs