Welcome to the tag category page for Data management!
AppFolio is a cloud-based property management software for the real estate industry. They offer a new integration marketplace called AppFolio Stack that provides rich functionality and deep data access. An online portal by AppFolio is available for residents whose management company uses AppFolio Property Manager. AppFolio is not free and uses a per unit, per month pricing model. Property managers with less than 50 units cannot implement AppFolio. Overall, AppFolio is designed to digitally transform real estate investment management with tools for fund management and syndication.
Databricks is an enterprise software company that combines data warehouses and data lakes into a lakehouse architecture. It was founded by the creators of Apache Spark and provides a web-based platform for working with Spark, offering automated cluster management and IPython-style notebooks. Databricks is used for processing, storing, cleaning, sharing, analyzing, modeling, and monetizing datasets, with solutions ranging from business intelligence to machine learning. It is available on two cloud platforms, Azure and AWS, and is infinitely scalable and cost-effective. The Databricks platform can handle all types of data and everything from AI to BI, making it popular among data scientists and data engineers.
TherapyNotes is a cloud-based mental/behavioral health software system that includes electronic health records (EHR), a patient portal, scheduling, medical billing, and more. It is designed for behavioral health professionals and is one of the most appealing aspects to new clinicians joining our practice. It ensures our documentation is compliant and up to date, allows for better communication with patients through the portal, and makes billing and payments easier.
MLflow is an open-source platform designed to streamline the machine learning development process. It includes components such as Tracking, which allows users to record and compare parameters and results from experiments, Projects, which packages code for reproducible runs on any platform, and Models, which manages and tracks models from training to production. MLflow is known for its versatility and ease of use, making it a popular choice for managing the entire lifecycle of a machine learning project. It provides capabilities for versioning models, tracking experimentation, and deploying models to production. Overall, MLflow is a powerful tool that simplifies and enhances the machine learning development process.
Homelab describes DIY, in-home computing and networking environments where hobbyists, IT pros and students run servers, networking gear and services for learning, testing and self-hosting. Common uses include virtualization, container platforms, network labs and home data centers for media, backups, development and cybersecurity practice. Communities such as r/homelab share builds, troubleshooting and project ideas, while smaller institutional “HomeLab” spaces can refer to dedicated incubators or bioscience accelerators. Homelabs emphasize hands-on skill growth in a low-risk environment, but bring practical considerations around power, cooling, noise and security. Deployments range from compact NAS and edge devices to rack-mounted clusters and GPU nodes for machine learning. The trend supports a market for components and appliances from networking vendors and hardware makers, and influences product lines aimed at prosumers and small offices.
Microsoft Dynamics 365 Business Central is a cloud-based ERP and business management solution for small and midsize businesses. It centralizes core business processes across finance, operations, supply chain, manufacturing, projects, and customer service on a single platform. The solution integrates with other Microsoft products to connect and streamline finance, sales, service, and operations across the organization.
A data catalog is an organized inventory and detailed list of all data assets in an organization that helps manage and discover data. It uses metadata management to enable data analysts, scientists, stewards, and other data consumers to find and understand datasets for extracting business value. It includes data from the World Bank's microdata, and open-source data catalog tools. Some examples of data catalog tools are Amundsen by Lyft and LinkedIn DataHub. The difference between a data catalog and a data warehouse is that the former helps find, understand, trust, and use data, while the latter stores structured data.
Businesses' data refers to the collection, storage, and analysis of data generated by companies through transactions, operations, and customer interactions. This data fuels analytics, AI, and decision-making, and is increasingly treated as a strategic asset with investments in data platforms, governance, and monetization models. The trend encompasses data infrastructure providers, analytics platforms, and enterprise software that enable the capture and utilization of business data.
