All analytics, even Datakwip’s, start with raw data. The Datakwip Analytics Platform allows us to import any and all available from our clients’ existing systems. This can be static files, existing databases, streaming data, and live data from your existing energy management system. Datakwip’s ingestion pipeline does not discriminate, it brings in any type of data and stores it immediately for backup in Amazon’s secure and reliable S3 storage.

Data Enrichment

After we import your static data, establish a connection to a database, or establish a persistent connection to a live data stream like an energy management system, we separate out each piece of information and pass it through our data enrichment layer. Data enrichment is the act of taking raw data and adding additional knowledge. This converts the data into information. Now, an update from a temperatures sensor isn’t just a number; it’s an update from a sensor in Room 203, in Building A, which is occupied by a Tenant. The room is served by an Air Handler, say AHU 2, which is in turn served by a chiller. This ability to add knowledge to data is what enables Datakwip to generate valuable insights that actual become actionable later in the pipeline.

Scalable Service Queue

You have a lot of data and Datakwip’s cloud platform has the power to grow with you. Our Scalable Service queue grows dynamically with all the data you can send its way. This means we get to focus on the value your data brings you, not increasing costs or maintenance need by the platform.

Datakwip Services

By using the Scalable Service Queue, we have the ability to continually develop new services that find new ways to deliver unharvested value back to our customers. This is where features like our Real-time Machine Learning Pipeline, our Real-time Rules Engine, and our Real-time Alerting Engine get their fuel

Machine Learning

Machine Learning represents a major paradigm shift in the way we analyze data. Machine Learning shifts operational work flows from a reactive to a proactive mode. Datakwip’s unique machine learning algorithms allow us to utilize your existing data to define proper operation for your building. We are then able to compare new, real-time data to these established baselines and determine how your building is operating relative to the best version of itself.

Data Lake

All this data has to go somewhere, and just like the rest of our platform, we need that somewhere to be scalable and extremely flexible. The Datakwip Data Lake stores all the data coming in to the platform and all the information coming out of it. It stores it in a way that makes it completely searchable so that we can provide the information we need to today as well as answer questions our customers will have in the future.

Visual Analytics

Driven by the power and flexibility of our Data Lake, the Datakwip Visual Analytics Platform enables us to present any information in any way. This means we get to work with our clients on what visualizations work best for their organization. Our Visual Analytics are available anywhere, anytime, and accessible through any web browser, so you control how the information is used and shared throughout your organization.

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