Leveraging AI and Machine Learning to Advance Interoperability in Healthcare

hitconsultant.net | January 16, 2020

Navigating the healthcare system is often a complex journey involving multiple physicians from hospitals, clinics, and general practices. At each junction, healthcare providers collect data that serve as pieces in a patient’s medical puzzle. When all of that data can be shared at each point, the puzzle is complete and practitioners can better diagnose, care for, and treat that patient. However, a lack of interoperability inhibits the sharing of data across providers, meaning pieces of the puzzle can go unseen and potentially impact patient health. True interoperability requires two parts: syntactic and semantic. Syntactic interoperability requires a common structure so that data can be exchanged and interpreted between health information technology (IT) systems, while semantic interoperability requires a common language so that the meaning of data is transferred along with the data itself.  This combination supports data fluidity.  But for this to work, organizations must look to technologies like artificial intelligence (AI) and machine learning (ML) to apply across that data to shift the industry from a fee-for-service where government agencies reimburse healthcare providers based on the number of services they provide or procedures ordered – to a value-based model that puts focus back on the patient.

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DATA ARCHITECTURE

Compass UOL and Furious Technologies announce partnership to provide data-driven pricing solutions

Compass UOL | December 24, 2021

Compass UOL, a global digital transformation company, and Furious Technologies, a North American revenue management and pricing optimization solutions provider, announced a strategic collaboration to provide online sellers in Latin America and USA with an integrated digital commerce solution. The partnership will combine advanced cloud-based data science and Compass UOL's digital next-generation platforms services portfolio with Furious Technologies' artificial intelligence models for data-driven pricing. It will enable organizations to innovate, make better data-driven decisions, solve business challenges, and increase business value. The objective is to seize insights and use data generated by customer digital interactions to help sellers optimize price and increase average value per customer by dynamically recommending relevant products and purchase incentives. Data-driven pricing, revenue management and higher margins While typical IT departments deal with an overload of demands and daily problems, which makes it difficult to meet business's innovation and expansion goals, Compass UOL and Furious Technologies believe that end-to-end customer journeys must be created in the cloud and optimized to ensure continuous growth. According to Alexis Rockenbach, CEO at Compass UOL, many companies are burdened by the need to increasingly use data to drive business decisions, solve supply chain issues and deal with the increasing material costs. As a result, they lack time and attention to customer touchpoints, or to sales and marketing overall. "Compass UOL and Furious Technologies combine experience, data science and proven methodologies to maximize revenue, deploy state-of-the-art technology, and mentor customer-oriented teams on business acceleration", concludes Rockenbach. Combining diverse US-based business teams, companies will be able to drive significant business development acceleration, having the potential to serve hundreds of B2B and B2C sellers in Latin America and the United States in the short term, and expand to other regions in the future. "Compass UOL and Furious' cloud and virtual structure offer customers a scalable solution to meet their immediate needs to both manage risk and combat disruption. This combination of flexibility and experience provides an optimal environment to perform and deliver business transformation solutions. This effort enables businesses to ensure that the entire online journey is set to improve service, revenue and exponentially expand customer reach." Ashley J. Swartz, CEO at Furious Technologies.

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BIG DATA MANAGEMENT

GoodData Adds Advanced Analytics to the Freshworks Marketplace

GoodData | January 06, 2022

GoodData, the leader in data and analytics infrastructure, today announced its new app on the Freshworks Marketplace to provide a powerful and scalable solution designed to accelerate the use and application of analytics for Freshworks customers. The Freshworks Marketplace hosts apps built by the Freshworks developer community. These apps make use of Freshworks products and partner solutions to create delightful experiences for businesses. The marketplace enables partners to reach Freshworks customers and serve them jointly. Freshworks Inc., (NASDAQ: FRSH) is a leading software company empowering businesses to delight its customers and employees. With the demand for cloud-native solutions and easy-to-use analytics on the rise, large companies with enterprise-grade data need vendors to provide analytics within their existing architecture. With the integration of GoodData’s analytics tool into its marketplace, Freshworks now provides enterprises with more options to unlock rich insights from within their data. Additionally, Freshworks can tap into GoodData's extensive experience powering analytics innovation in the Customer Experience Management (CX) space. The integration between GoodData and Freshworks will help provide valuable analytics for customer support teams to better understand the strong and weak points of their customer facing team and help to better customer experiences. “For data leaders to meet the challenges of today’s hyper-competitive market, they have to reinvent the way they think about and utilize data at every layer of their organization. Freshworks recognized the need for its marketplace to offer an analytics platform that tells a customer-centric, accessible story with data, and our solutions make it possible for Freshworks to implement immediately and scale​​. This app will make it easy for enterprises to understand and benefit from modern analytics, and it’s just the beginning of a fruitful partnership between our two cloud-first companies. We are excited to collaborate with Freshworks.” GoodData founding CEO Roman Stanek Freshworks helps some of the largest, industry-leading companies in the world — ranging from healthcare to financial services, and more — realize value from their software. Already providing customers with low-code development and ​​custom apps within their marketplace to extend their product capabilities at scale, Freshworks now partners with GoodData to provide customers with more options to unlock their inherent value of data as a strategic asset. “Analytics is a key part of improving user experience for any technology. As we continue to grow, we need an ISV partner who not only understands our business model but also one that could purpose-build apps for the modern business software users,” said Hérve Danzelaud, VP of Global Partnerships at Freshworks. “GoodData’s state-of-the-art analytics stack is the perfect tool to quickly bring nearly real-time analytics into our current offerings and helps enterprises to access vital insights in this new age of data.” The marketplace app is the first step in an ongoing partnership between GoodData and Freshworks, and the companies will continue to work together to provide actionable and easy to use analytics to Freshworks customers. The partnership will expand Freshworks’ offering with advanced analytics and business insights. About GoodData GoodData is on a mission to break data silos. Real-time, open, secure, and scalable, GoodData’s leading composable data and analytics platform provides a single source of truth across organizations and to their customers. To this day, GoodData has helped more than 140,000 of the world’s top businesses deliver on their analytics goals and scale their use cases — from self-service and embeddable analytics, to machine learning and IoT.

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DATA ARCHITECTURE

VAST Data Announces Newest Feature Releases

VAST Data | May 23, 2022

VAST Data, the data platform company for the AI-powered world, today announced the latest versions of Universal Storage, bringing enhanced enterprise security features, performance and scale to its flagship software offering. With an install base of multiple exabytes and an annual growth rate of 300%, customers are continually challenging VAST with new feature requests to power their data-intensive use cases. This release, in total, represents more than 30 new features that have been directly requested by VAST customers. Testament to VAST’s distinguished R&D team, the average turnaround of “feature request to code” is four months. “Since our founding, we have always maintained a customer-first mindset, continuously adding new features and functionality at a rapid pace to solve their ever-growing and changing application needs. Ultimately, we work to foster a close collaboration with our customers whose use cases are our product’s North Star. This level of agility is never seen from legacy providers of data infrastructure. Our responsive approach not only helps our customers manage their data easier, it also creates long-term business partnerships with customers and the broader market that is good for VAST.” Jeff Denworth, co-founder of VAST Data VAST’s Universal Storage data platform provides customers with a cloud-native containerized storage architecture, and eliminates storage tiering to unleash insights on their massive reserves of data. Versions 4.2 and 4.3 expand on an already stellar feature set, while continuing to deliver increased functionality, scalability and security features — and still improving system performance. Notable features in the latest release include: Enhanced Security VAST expands protection against ransomware attacks with Object Locks. Customers can set policies on buckets and objects to make them immutable, preventing users and applications from deleting or modifying an object before its expiry. Admins can also use S3 bucket policies to define permissions, enabling secure identity and access management. Now generally available in Universal Storage, Indestructible Snapshots provide an additional layer of protection that safeguards immutable snapshots and policies from sophisticated external or internal attackers. Compliance with Federal Information Processing Standards (FIPS) 140-2, using validated cryptographic libraries for encryption at rest. Flexible Cloud Data Management One platform that integrates S3 bucket management for integrated file and object storage. Customers can easily share data between file and object storage protocols — Universal Storage is the only platform that provides this functionality, giving customers the best of both worlds. Check out this blog post and deep-dive demo. Further improvements to VAST’s centralized Uplink Cloud Management system include integration with Zendesk, providing customers with a smooth and intuitive support experience to create, track and manage their support tickets. For more information about VAST’s Uplink Cloud Management service, check out this blog post and deep-dive demo. Enhanced Performance for Secure Protocols Support for NFS4 over RDMA, delivering a performance boost for NFS4. By extending NFS4 over RDMA, VAST is increasing speed while providing customers with an enhanced security blanket via a Kerberized connection. VAST is the only vendor to accelerate NFS4 with RDMA, making it possible to power high-performance high-scale HPC, AI, media and analytics workloads with a simple and secure client interface. About VAST Data VAST Data delivers the data platform at the heart of the AI-powered world, accelerating time-to-insight for workload-intensive applications. The performance, scalability, ease of use and cost efficiencies of VAST’s software helps enterprise organizations overcome the historic barriers to building all-flash data centers. Founded in 2019, VAST is the fastest-selling data infrastructure startup in history.

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DATA SCIENCE

Introducing Neo4j Graph Data Science as a Service

Neo4j | April 13, 2022

Neo4j®, the world's leading graph data platform, announced Neo4j Graph Data Science, the company's comprehensive graph analytics workspace built for data scientists, is now available with new and enhanced capabilities, and as a fully managed cloud service called AuraDS. AI and machine learning (ML) have propelled the use of predictive data architectures and their application across a broad range of use cases like recommendation engines, fraud detection, and customer 360 scenarios. The accuracy of these models is highly correlated to the completeness of context. Neo4j Graph Data Science is designed to make it easy for data scientists to achieve greater predictive accuracy with comprehensive graph analysis techniques. Users can improve models through a library of graph algorithms, ML pipelines, and data science methods. Neo4j Graph Data Science has been widely adopted and is trusted to perform at scale, easily handling hundreds of billions of nodes and relationships. "Neo4j Graph Data Science offerings help developers offer better predictions and stronger recommendation engines to business users. Customers can now deploy Graph Data Science on Google Cloud's trusted, global infrastructure, gaining the ability to seamlessly scale based on business needs, and bringing their data closer to BigQuery and Google Cloud's capability in AI, ML, and analytics. Ritika Suri, Director, Technology Partnerships at Google "More software developers are looking to data science for ways to offer better predictions and stronger recommendation engines to users. Google Cloud and Neo4j Graph Data Science products help software developers and data scientists who are building the world's next set of intelligent applications by leveraging the power of graph algorithms to bring context to data and improve their models," said Suri. Neo4j Graph Data Science makes it easy for data scientists to work within their existing data pipeline of tools across their ecosystem. Data scientists can use Neo4j Graph Data Science on-premises, and now as a fully managed SaaS solution via Neo4j AuraDS. According to Zack Gow, CTO of Orita, Neo4j Graph Data Science has enabled his team to be more responsive to customer needs. "Scale is always top of mind for us because we're processing data that comes from our customers. We never know just how big a customer's data set will be and we chose Neo4j because we knew it could handle the scaling of an order of magnitude more than what we were expecting," Gow said. "Even in the early days, when we were trying out a bunch of tools, Neo4j worked for us immediately. Some of the tools we looked at didn't work at all. Neo4j Graph Data Science got our data into a graph so we could start doing the data science part quickly. As a start up, we don't have time to waste on tools that are cumbersome." Matthew Bernardini, CEO of Zenapse, shared the impact of Neo4j Graph Data Science on his business. "We chose Neo4j Graph Data Science on AuraDS because it is a completely managed, cloud-based infrastructure combined with an elegant and user-friendly set of tools and extensive library of production-ready data science algorithms that gives us confidence in our platform and allows us to focus on our data and application development," said Bernardini. "Neo4j Graph Data Science makes it easy to quantify the relationships and similarities that exist in the digital world and to surface new insights about these connected relationships." Neo4j AuraDS: Graph Data Science on Google Cloud Platform Neo4j AuraDS is the power of Graph Data Science available as a fully managed service. It includes access to over 65 graph algorithms in a single workspace so data scientists can experiment faster. In-graph ML models and the native Python client help increase productivity and simplify workflows. Neo4j AuraDS is available first on Google Cloud's secure, global, and highly performant structure, and can be paid for with existing Google Cloud commitments or with a credit card. In addition to the Graph Data Science core functionality, AuraDS customers benefit from: Simple, powerful workflow: A drag-and-drop UI to model and import data into a graph. Scale up and down: Manage access to high compute hardware on-demand as needs change. Automated operations: Workloads are monitored, patched, and backed up behind the scenes without any user action. MLOps support: Persist, publish, and restore models without interruptions from restarts. Predictable cost: Manage costs with pay-as-you-go pricing and the option of pausing unused instances. One-click backup: Take a snapshot of instances, models, and in-memory graphs in one click. For guidance and reference architectures on how to get started using Neo4j AuraDS with VertexAI, see Use graphs for smarter AI with Neo4j and Google Cloud Vertex AI. More About Neo4j Graph Data Science and AuraDS To learn more about Neo4j Graph Data Science as a service, AuraDS, read this blog post or tune in to an upcoming webinar, "What's New in Graph Data Science: Faster and Easier Than Before," on Tuesday, April 26, 2022. About Neo4j Neo4j is the world's leading graph data platform. We help organizations – including Comcast, ICIJ, NASA, UBS, and Volvo Cars – capture the rich context of the real world that exists in their data to solve challenges of any size and scale. Our customers transform their industries by curbing financial fraud and cybercrime, optimizing global networks, accelerating breakthrough research, and providing better recommendations.

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M brain big data trends infographic. 1. BIG D/ TA ANALYTICS TRENDS IN 2014 What you need to know. 0 SPEED WILL BE OF ESSENCE 'H N. M brain big data trends infographic. The big data analytics market 2013 2023. Hace 3 años Big Data and Analytics - Why Should We Care?

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