Deploying modern tool sets and leveraging industry technology experts
Machine learning is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. The technological advances in storage and processing power have enabled some innovative products based on machine learning, such as Netflix’s recommendation engine, self-driving cars, and online home sales. Machine learning is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of new products. Machine learning has become a significant competitive differentiator for many companies and one of many reasons Evergreen Residential leverages this technology. We use a Semi-supervised machine learning which data scientists and analysts may feed an algorithm mostly labeled data, but the model is free to explore the data on its own and develop its own understanding of the data set to push out informed data decisions and reporting.
Software built for the industry-by-industry veterans
Evergreen Residential deploys a modern infrastructure platform. Partnering with software development companies we have built the core tools that are needed to increase NOI, lower friction of optimally utilizing assets, and remove any reliance on industry legacy systems. We are constantly asking the questions why, how, when?
- Why was an ERP or PMS designing this way
- How can we improve on the way legacy systems work for our industry
- When can we deploy better solutions
Why settle for systems that were built with the Multifamily investment class in mind first and SFR second? The nuances of the different asset classes are noticeable and require different thought processes in how you research, invest, and manage them.
A data warehouse focuses on collecting data from multiple sources to facilitate broad access and analysis. They specialize in data aggregation and providing a longer view of an organization’s data over time. A data warehouse is optimized to store large volumes of historical data and enables fast and complex querying of that data. Standard operational databases focus on transactional functions such as real-time data updates for ongoing business processes. Data warehousing has two key functions. First, it serves as a historical repository for integrating the information and data that is needed by the business, which may come from a variety of different sources. Second, it serves as a query execution and processing engine for that data, enabling end users to interact with the data that is stored in the database. Evergreen Residential is excited to partner with Snowflake for our DW. Snowflake is a Data Warehouse-as-a-Service solution developed for the cloud. Its data architecture uses the elastic, scalable Azure Blobs Storage as its internal storage engine, Azure Data Lake to store unstructured, structured, and on-premise data ingested via the Azure data factory. Snowflake provides data security using Amazon S3 policy controls, Azure SAS tokens, SSO, and Google Cloud Storage access permissions. It allows you to scale your storage depending on your storage needs. Thus, a Snowflake data warehouse will let you enjoy scalability, security of your data, and many other benefits. Snowflake offers native connectivity with multiple BI, data integration, and analytics tools such as Azure Data Factory, IBM Cognos, Oracle Analytics Cloud, Google Cloud, Fivetran, and many others.