Vivint Solar Supports Entire Enterprise MicroStrategy Cloud Platform on AWS
Company Size
1,000+
Region
- America
Country
- United States
Product
- MicroStrategy Cloud Platform
- Amazon VPC
- Amazon RDS
- Amazon EC2
- Amazon CloudFormations
Tech Stack
- MicroStrategy
- AWS
- Amazon VPC
- Amazon RDS
- Amazon EC2
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Infrastructure as a Service (IaaS) - Cloud Computing
- Infrastructure as a Service (IaaS) - Cloud Storage Services
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Renewable Energy
- Utilities
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Remote Asset Management
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
- System Integration
About The Customer
Vivint Solar is a leading solar company dedicated to improving how households create power. With 4,000+ energy experts in 21 states across the U.S., Vivint has served 106,000+ customers since its founding in 2011. Their award-winning customer service begins with a comprehensive solar panel consultation, customized solar design, services for processing all required paperwork, and quick installation.
The Challenge
Started in 2011, Vivint Solar was a small start-up organization that needed a robust sales team to generate revenue and establish a strong customer base. They hired a team of analysts to support sales operations. These analysts, spread across the organization, relied on Excel to extract insights, wrangle data, and produce reports. This legacy solution worked well in Vivint’s early years when it had less data to handle. “As the company grew and our volume of customers grew, [this Excel-based solution] didn’t scale,” said Jed Rampton, Data Architect, Vivint Solar. Soon, their Excel sheets took hours to calculate and their teams spent more time debating whose numbers were correct than making a decision. Vivint needed a fast and flexible analytics platform that could scale with their rapidly growing business.
The Solution
Vivint realized that MicroStrategy met their technical needs while also offering an intuitive interface that could be accessed anywhere (e.g. mobile, browser, desktop). At the same time, Vivint made an early decision to partner with Amazon for their data center needs instead of hosting an on-premise data center. With these requirements in mind, Vivint made a quick and confident decision to invest in the MicroStrategy Cloud Platform on AWS. “We were really excited, really thrilled to hear that MicroStrategy had built this tool to quickly deploy MicroStrategy instances in AWS and then, after they’re deployed, to manage those instances for us,” said Jed. Vivint’s small business intelligence team had a large sales team to support, so they didn’t have the bandwidth to manage their instances. MicroStrategy did that for them so users could focus on delivering insights to make intelligent decisions. The MicroStrategy Cloud Platform easily deployed into the customers’ existing Amazon VPC. This made security easy for their small team since they didn’t have to change any of their existing configurations. Then, Amazon CloudFormations deployed MicroStrategy on top of an EC2 instance, which automatically connected to a separate Amazon RDS to provide telemetry and data storage. In just a week, Vivint deployed a fully configured, multi-node environment through the MicroStrategy Cloud Platform. They also had a development instance connected to all their data sources so they could blend disparate sources into rich reports. Vivint can instantly scale these instances up or down based on peak business load times, saving them costs in Amazon infrastructure.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
IoT Solutions for Smart City | Internet of Things Case Study
There were several challenges faced: It is challenging to build an appliance that can withstand a wide range of voltage fluctuations from as low at 90v to as high as 320v. Since the device would be installed in remote locations, its resilience was of paramount importance. The device would have to deal with poor network coverage and have the ability to store and re-transmit data if networks were not available, which is often the case in rural India. The device could store up to 30 days of data.
Case Study
Vestas: Turning Climate into Capital with Big Data
Making wind a reliable source of energy depends greatly on the placement of the wind turbines used to produce electricity. Turbulence is a significant factor as it strains turbine components, making them more likely to fail. Vestas wanted to pinpoint the optimal location for wind turbines to maximize power generation and reduce energy costs.
Case Study
Automation of the Oguz-Gabala-Baku water pipeline, Azerbaijan
The Oguz-Gabala-Baku water pipeline project dates back to plans from the 1970’s. Baku’s growth was historically driven by the booming oil industry and required the import of drinking water from outside of the city. Before the construction of the pipeline, some 60 percent of the city’s households received water for only a few hours daily. After completion of the project, 75 percent of the two million Baku residents are now served around the clock with potable water, based on World Health Organization (WHO) standards. The 262-kilometer pipeline requires no pumping station, but uses the altitude differences between the Caucasian mountains and the capital to supply 432,000 m³/d to the Ceyranbatan water reservoir. To the people of Baku, the pipeline is “the most important project not only in 2010, but of the last 20 years.”
Case Study
GPRS Mobile Network for Smart Metering
Around the world, the electricity supply industry is turning to ‘smart’ meters to lower costs, reduce emissions and improve the management of customer supplies. Smart meters collect detailed consumption information and using this feedback consumers can better understand their energy usage which in turn enables them to modify their consumption to save money and help to cut carbon emissions. A smart meter can be defined in many ways, but generally includes an element of two-way communication between the household meter and the utility provider to efficiently collect detailed energy usage data. Some implementations include consumer feedback beyond the energy bill to include online web data, SMS text messages or an information display in consumers’ premises. Providing a cost-effective, reliable communications mechanism is one of the most challenging aspects of a smart meter implementation. In New Zealand, the utilities have embraced smart metering and designed cost effective ways for it to be implemented. The New Zealand government has encouraged such a move to smart metering by ensuring the energy legislation is consistent with the delivery of benefits to the consumer while allowing innovation in this area. On the ground, AMS is a leader in the deployment of smart metering and associated services. Several of New Zealand’s energy retailers were looking for smart metering services for their residential and small business customers which will eventually account for over 500,000 meters when the multi-year national deployment program is concluded. To respond to these requirements, AMS needed to put together a solution that included data communications between each meter and the central data collection point and the solution proposed by Vodafone satisfied that requirement.
Case Study
Siemens Wind Power
Wind provides clean, renewable energy. The core concept is simple: wind turbines spin blades to generate power. However, today's systems are anything but simple. Modern wind turbines have blades that sweep a 120 meter circle, cost more than 1 million dollars and generate multiple megawatts of power. Each turbine may include up to 1,000 sensors and actuators – integrating strain gages, bearing monitors and power conditioning technology. The turbine can control blade speed and power generation by altering the blade pitch and power extraction. Controlling the turbine is a sophisticated job requiring many cooperating processors closing high-speed loops and implementing intelligent monitoring and optimization algorithms. But the real challenge is integrating these turbines so that they work together. A wind farm may include hundreds of turbines. They are often installed in difficult-to-access locations at sea. The farm must implement a fundamentally and truly distributed control system. Like all power systems, the goal of the farm is to match generation to load. A farm with hundreds of turbines must optimize that load by balancing the loading and generation across a wide geography. Wind, of course, is dynamic. Almost every picture of a wind farm shows a calm sea and a setting sun. But things get challenging when a storm goes through the wind farm. In a storm, the control system must decide how to take energy out of gusts to generate constant power. It must intelligently balance load across many turbines. And a critical consideration is the loading and potential damage to a half-billion-dollar installed asset. This is no environment for a slow or undependable control system. Reliability and performance are crucial.
