Tag: Amazon S3

Take an in-depth view of the cloud migration and data platform modernization process for Flipboard, which engaged Mactores Cognition for a thorough assessment of the self-managed platform and help migrating existing data workloads to a fully managed Amazon EMR serverless big data platform. The process streamlined Flipboard’s distributed database capabilities, allowing the social media platform to support user spikes at scale, maximize throughput performance, and prepare to expand the user base exponentially.

Infusing machine learning into core business processes such as credit scoring creates a competitive edge for banks and financial services institutions. It does not require a data science team, expertise, or platform rollout. Explore an ML-based credit-decisioning model built by ElectrifAi in collaboration with AWS whose model rapidly determines the creditworthiness of a SME, and data-driven, actionable insights reduce the overall processing cost and are consistent and free from any potential human biases.

Enterprises require the ability to be proactive on modern governance challenges. The difficulty is knowing what data you have, where it’s located, its business value or risk to the organization, and how it can be protected. The Smarsh Enterprise Platform enables companies to capture, retain, analyze, and act on the “signals” in communications that are most critical to the business. These include compliance and brand risks and may expand to include security threats, cultural indicators, untapped revenue opportunities, and more.

DevSecOps teams are responsible for providing enhanced infrastructure observability while ensuring they have the ability to respond to security events in a matter of minutes across the entire organization. To address this challenge, Sumo Logic and AWS collaborated to build a solution that provides end-to-end security and incident management (SIEM) across an enterprise using AWS Organizations. This SIEM solution is based on the AWS Security Reference Architecture.

Featurization is one of the most difficult problems in machine learning. Learn how graph features engineered in Neo4j can be used in a supervised learning model trained with Amazon SageMaker. These novel graph features can improve model performance beyond what’s possible with more traditional approaches. Together, these components offer a graph platform that can be used to understand graph data and operationalize graph use cases.

Digital food ordering is one of the most rapidly growing global industries today. Cognizant’s OrderServ 2.0 platform is an omni-channel digital ordering platform designed for the restaurant and food services industries. It has built-in connectors for seamless integration with restaurant point-of-sale (POS) systems, master data management, payments services, loyalty programs, and other business applications. OrderServ 2.0 is offered as a SaaS platform hosted on AWS.

A digital journey is of strategic importance for many organizations, and digital transformation enabled by cloud technologies has increased efficiency and raised productivity with improved stakeholder experiences. To achieve these outcomes, transformation initiatives need to be holistic, interlinked, and inclusive. Learn how to supercharge customer experiences and make your contact center future-ready by leveraging HCLTech’s Fluid Contact Center Intelligence (Fluid CCI) and AWS AI/ML services.

This post explores an asynchronous pattern for ingesting data from legacy systems, collecting it into projections, and aggregating it into single views. The purpose of this solution is to decouple the source systems where data is stored from the external channels that request data—ensuring both offloading of source systems and making data available to channels 24/7 and in near real-time. The proposed solution is a simplification of the high-end architecture of Mia-Platform Fast Data.

Provectus, an AWS Premier Tier Services Partner with the Data and Analytics Competency, helps clients resolve issues of their legacy, on-premises data platforms by implementing best practices for the migration and optimization of Amazon EMR workloads. This post examines the challenges organizations face along the path to a successful migration, and explores best practices for re-architecting and migrating on-premises data platforms to AWS

While utilities have historically been rich with data from customers, programs, and assets, many organizations often manage data in siloes. Source data can also be disorganized, with deficiencies in defined quality assurance and quality control processes. Learn how utilities are successfully embracing Accenture’s data-led transformation (DLT) and leveraging accelerators powered by AWS to reach their business objectives and meet regulatory obligations.