Tag: Amazon Athena

Leveraging data to make better decisions is critical for driving optimal business outcomes. Palantir empowers organizations to rapidly extract maximum value from one of their most valuable assets—their data. Palantir Foundry solves for the real-world application of AI, and not how it works in the lab. Effective AI is impossible without a trustworthy data foundation, a representation of an institution’s decisions, and the infrastructure to learn from every decision made.

Cognizant is providing consulting and execution services for SAP customers to migrate the SAP landscape from on-premises to AWS, with SAP S/4HANA implementation on AWS combining SAP S/4HANA conversion and migration to AWS in a single step using the Cognizant migration factory called SmartMove. This solution provides a risk-free, comprehensive solution to transform customers’ SAP landscape into one that’s intelligent enterprise-ready.

With exponential increases in the amount of visual data such as images and videos being generated, image analytics is fast becoming a major business driver for many organizations. The Deloitte Image Recognition Framework is a cloud-based image recognition platform leveraging machine learning to automatically distinguish between two images. It helps customers deploy image recognition and analytics solutions and customize it per their business requirements.

Big datasets have traditionally been locked on-premises because of data gravity, making it difficult to leverage cloud-native, serverless, and cutting-edge technologies provided by AWS and its community of partners. Modernizing an on-premises analytics platform takes time, effort, and careful planning. Explore the challenges of migrating large, complex, actively-used structured datasets to AWS and how the combination of WANdisco LiveData Migrator, Amazon S3, and AWS Glue Data Catalog overcome those challenges.

Data security has always been an important consideration for organizations when complying with data protection regulations. Protegrity, an AWS ISV Partner and global leader in data security, has released a serverless User Defined Function (UDF) that adds external data tokenization capabilities to the Amazon Athena platform. Learn how customers can use the Protection Athena Protector UDF to tokenize or detokenize data at scale.

Patch management is a continuous cybersecurity process that includes identifying, reporting, and fixing the system vulnerabilities. An operating system’s patches are part of essential preventative maintenance, necessary to keep machines up-to-date, stable, and safe from malware and other threats. Learn how Tech Mahindra‘s automated patching solution helps and ensures every server on the infrastructure system’s network is up-to-date by patching quickly and efficiently.

Application modernization requires a holistic approach, and Cloudwiry enables optimization and modernization of cloud deployments by evaluating AWS services involved. Learn how the Cloudwiry Enterprise platform can help your organization make informed decisions about application modernization. This post also takes a deeper look into specific examples of how Cloudwiry has helped customers optimize their cloud usage on AWS.

There is broad acceptance that AI and ML will help improve health outcomes for patients, and make healthcare more affordable. Data Science as a Service (DSaaS) from Change Healthcare is a secure, managed, healthcare data science platform that customers can leverage the embedded datasets and load their own datasets to be linked to deliver transformative and compliant insights. Learn how Change Healthcare built DSaaS to address the needs of practitioners developing AI/ML algorithms.

Running virtual machines with databases or datastores on VMware Cloud on AWS lets you use the same management tools and VMs as on your on-premises VMware vSphere environment. You can easily extend these workloads to the cloud and take advantage of AWS on-demand delivery, global footprint, elasticity, and scalability. Learn how VMware Cloud on AWS brings these datasets closer to AWS Analytics Services, making it easier to use services to draw meaningful insights from business data.

Achieving “speed of thought” or instant analytics on large data sets is a key challenge for business intelligence platforms. Traditionally, data engineers would design and deliver an optimized, aggregated subset of the data to a data warehouse to drive the visualization. This can often take weeks of development and testing or incur significant infrastructure costs. Learn how Indexima uses machine learning and hyper indexes to automate this process and accelerate analytics by up to 1000x across a full data set on Amazon S3.