PHEMI Health DataLab Integrations

Amazon Web Services (AWS) is the world’s most comprehensive cloud platform, trusted by millions of customers across industries. From startups to global enterprises and government agencies, AWS provides on-demand solutions for compute, storage, networking, AI, analytics, and more. The platform empowers organizations to innovate faster, reduce costs, and scale globally with unmatched flexibility and reliability. With services like Amazon EC2 for compute, Amazon S3 for storage, SageMaker for AI/ML, and CloudFront for content delivery, AWS covers nearly every business and technical need. Its global infrastructure spans 120 availability zones across 38 regions, ensuring resilience, compliance, and security. Backed by the largest community of customers, partners, and developers, AWS continues to lead the cloud industry in innovation and operational expertise.

Microsoft's Azure is a cloud computing platform that allows for rapid and secure application development, testing and management. Azure. Invent with purpose. Turn ideas into solutions with more than 100 services to build, deploy, and manage applications—in the cloud, on-premises, and at the edge—using the tools and frameworks of your choice. Continuous innovation from Microsoft supports your development today, and your product visions for tomorrow. With a commitment to open source, and support for all languages and frameworks, build how you want, and deploy where you want to. On-premises, in the cloud, and at the edge—we’ll meet you where you are. Integrate and manage your environments with services designed for hybrid cloud. Get security from the ground up, backed by a team of experts, and proactive compliance trusted by enterprises, governments, and startups. The cloud you can trust, with the numbers to prove it.

Power BI is a business intelligence platform that enables users to analyze data using AI-driven tools and intuitive report creation. It consolidates data from various sources into OneLake, creating a centralized data source. This platform aids in embedding actionable insights into applications like Microsoft 365, aiding decision-making. Power BI integrates with Microsoft Fabric, enhancing data management. It offers scalability to handle large data volumes and integrates seamlessly with Microsoft services. Its AI capabilities efficiently identify patterns and generate insights. Power BI ensures data security and compliance. Its Copilot feature allows rapid report generation. Additionally, Power BI Pro offers self-service analytics, and its free version includes data modeling and visualization tools. It's known for unified data management, empowering users with accessibility and training resources. Power BI has demonstrated a significant ROI and economic benefit, as evidenced in a Forres

Tableau, now enhanced with AI-powered capabilities and integrated with Salesforce, is an advanced analytics platform that helps businesses turn data into actionable insights. With Tableau Next, users can unlock the full potential of their data by accessing trusted AI-driven analytics. Whether deployed in the cloud, on-premises, or natively within Salesforce CRM, Tableau enables seamless data integration, powerful visualizations, and collaboration. The platform is designed to support organizations of all sizes in making data-driven decisions, while fostering a Data Culture through easy-to-use, intuitive tools for analysts, business leaders, IT leaders, and developers alike.

The Apache Hive data warehouse software facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage. A command line tool and JDBC driver are provided to connect users to Hive. Apache Hive is an open source project run by volunteers at the Apache Software Foundation. Previously it was a subproject of Apache® Hadoop®, but has now graduated to become a top-level project of its own. We encourage you to learn about the project and contribute your expertise. Traditional SQL queries must be implemented in the MapReduce Java API to execute SQL applications and queries over distributed data. Hive provides the necessary SQL abstraction to integrate SQL-like queries (HiveQL) into the underlying Java without the need to implement queries in the low-level Java API.

Apache Ranger™ is a framework to enable, monitor and manage comprehensive data security across the Hadoop platform. The vision with Ranger is to provide comprehensive security across the Apache Hadoop ecosystem. With the advent of Apache YARN, the Hadoop platform can now support a true data lake architecture. Enterprises can potentially run multiple workloads, in a multi tenant environment. Data security within Hadoop needs to evolve to support multiple use cases for data access, while also providing a framework for central administration of security policies and monitoring of user access. Centralized security administration to manage all security related tasks in a central UI or using REST APIs. Fine grained authorization to do a specific action and/or operation with Hadoop component/tool and managed through a central administration tool. Standardize authorization method across all Hadoop components. Enhanced support for different authorization methods - Role based access control etc.

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page. Apache Hadoop 3.3.4 incorporates a number of significant enhancements over the previous major release line (hadoop-3.2).

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

Manage and secure the data lifecycle from the Edge to AI in any cloud or data center. Operates across all major public clouds and the private cloud with a public cloud experience everywhere. Integrates data management and analytic experiences across the data lifecycle for data anywhere. Delivers security, compliance, migration, and metadata management across all environments. Open source, open integrations, extensible, & open to multiple data stores and compute architectures. Deliver easier, faster, and safer self-service analytics experiences. Provide self-service access to integrated, multi-function analytics on centrally managed and secured business data while deploying a consistent experience anywhere—on premises or in hybrid and multi-cloud. Enjoy consistent data security, governance, lineage, and control, while deploying the powerful, easy-to-use cloud analytics experiences business users require and eliminating their need for shadow IT solutions.