Businesses and consumers are dealing with an explosion of data available for collecting, analyzing and using to make decisions. The speed, amount, variety and richness of data generated by new sources such as wearables, mobile apps, social media, sensors, and various connected devices outpaces the ability of humans to understand, analyze, draw insights from, and act on it. The Internet of Things (IoT) will further accelerate the impact of data on decision making process by providing even more unique and unprecedented data regarding consumer behavior.
Organizations are demanding more from their data analytics efforts and want immediate insights that can drive decision making. In more and more real life applications data analytics, data mining, and related paradigms have become mission critical. Closeloop Technologies provides data analytics consulting services using latest technologies such as big data, machine learning, deep learning and natural language processing as well as open, standard-based solutions using APIs, Micro-services, and programming languages. Our team is expert at data collection techniques, data processing, data cleansing and creating data warehouses. We also excel at data modeling and generating algorithms as well as the data presentation and visualization layers.
Omnidian Inc collects, monitors and analyzes data for energy generated by solar power systems installed on thousands of homes in North West US. The company's business model is based on an end-to-end solar power monitoring, field service repair, and performance guarantee product for the life of solar power systems. To achieve this Omnidian needed a fully integrated custom platform capable of collecting data from various partners, storing that data in specific format, running regular data analytics programs and reporting on anomalies.
Closeloop designed and engineered a full featured platform for Omnidian called Resolv (Java, Spring framework, MySQL, React.js, AWS EC2, AWS S3, Amazon RDS) which is capable of importing data from multiple sources in multiple formats. This data goes through pre-processing and is then stored in multiple customer-specific databases. Post-processing consists of a series of software programs running in parallel to analyze the data and store the results in separate data warehouses. The front-end application consists of multiple dashboards, reports and graphs which are generated in real-time and can be configured by the app administrator to provided finely tune data for decision making process. Resolv also integrates with field service system (Zendesk) and can create support cases automatically based on parameters defined for different scenarios.
The first iteration of the platform was designed, coded, tested and delivered in 4 months. Since than two additional versions have been released enhancing the capabilities and enabling integrations with additional partners.
Understanding the business model and the value flow was critical to even begin working.
Understanding the data flows. Detailed & accurate documentation of data types and models.
Using the right tools for right job. Java, Spring framework, MySQL, React.js, AWS EC2, AWS S3, Amazon RDS.
Specialists for each area - database engineers, front-end developers, mobile engineers.
Start right; maintain momentum; track/report progress; make smart decisions.
Iterative testing ensures quality control, good output and final acceptance.
Reducing ambiguity, managing accurate expectations and maximizing process stability.
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