Archives

Manage multiple devices installed at multiple customer locations

Client: A US-based multinational company manufacturing technical products. 

Problem:  The client needed to connect their product with the cloud using IoT to allow their product to be remotely managed, to gain insights on the use of the device and allow the product to be upgraded via over the air update (OTA). The goal was to reduce operating costs, increase device up­time & enhance device security through this remote connection.

VT’s Solution: We developed a system that deployed content dynamically on any device, allowing the client to manage their devices and device settings from anywhere in the world. This solution can be thought of having three distinct yet connected components.

  1. Device Management: Provides complete control over your devices, allowing you to lock the interface and open ports down to help prevent tampering.
  2. Dashboard: Provides a real time, easy to understand graphical presentation of key device metrics and data. Users can see CPU activity and analytics as a measure of general device health, as well as a listing of all high priority alerts and notifications.
  3. OS Management: From Operating System (OS) upgrades and security patches to driver updates, new hardware controls and many more operating system level updates, all can be applied remotely with ease.

By utilizing the solution, we were able to reduce operating costs, increase device up time, enhance device security, allowed customers to leverage existing investments in mobile and web assets, and introduced a modular and scalable system which integrates with existing content management system platforms & MDM tools. 

Key Points:

  • Achieved client’s business objectives, by implementing an IoT system on top of client’s in-house systems, to allow them to connect, monitor and upgrade their devices remotely.  
  • Created an IoT system that allowed the user to remotely control multiple devices from anywhere in the world, allowing dynamic content to be pushed, or to upgrade device OS.  
  • Provided real time metrics and data through dashboards and visualizations to monitor device health, and measure device usage. 
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Modernizing Medical Machine Management and Maintenance

Client: One of the largest original equipment manufacturers (OEMs) of medical, industrial and security X-ray machines in India.

Problem: The client needed methods for their customers to monitor and manage their X-ray machines, while also providing accurate measures for vacuum tube replacement in the machines. Another issue is the damage that a faulty X-ray machine can cause if it is not identified. The problem as such had three parts:

  1. Asset tracking: Hospitals and diagnostic centers with large deployment of X­ray machines often have issues in accurately tracking usage, availability and location of these machines.
  2. Machine fault monitoring: Exposure to large and uncontrolled doses of X-rays can cause serious cell damage. Machine faults, if not rectified, can expose patients and/or operators to large and uncontrolled X-rays.
  3. Predictive maintenance for vacuum tubes: Vacuum tubes used in X-­ray machines have a limited life and need to be replaced after a certain number of X-ray photos have been taken. High level of human interaction in data collection & maintenance inevitably leads to inaccurate and unreliable data.

VT’s Solution: A hardware unit with a GSM module was installed within the X-ray control panel, this component utilized the machine serial number to generate a geotag for the device. Pushing information regarding the x-ray machine to the cloud, we also implemented a system that sent text messages to the client and client’s customers to indicate the current functioning of the machine. The cloud services provide analytical processing of the data, where prediction models were used to power predictive maintenance for the vacuum tubes. The client and the client’s customers can also view the performance and functioning of the machine through the custom web application, displaying easy to understand dashboards and visualizations. 

Key Points:

  • Achieved client’s business objectives by introducing IoT services with cloud and analytical systems, allowing the client to monitor the health of their device, and predict maintenance. 
  • Installed IoT devices to monitor location and condition of X-ray machines, providing real-time data about the functioning of the machine. 
  • Deployed Cloud to perform advanced analytics on the data from each machine, performing predictive analytics to forecast maintenance.
  • Built easy to understand dashboards and visualizations for quick actions to be taken in cases of faulty functioning or replacement of vacuum tubes. 
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Introduce Asset Monitoring and Predictive Maintenance in Your Business

Client: A US-based multinational company in industrial manufacturing. 

Problem: The client is one of the largest suppliers of industrial and environmental machinery to multiple other industries. One of their major products are pumps that are utilized in power, oil, gas, chemical and other industries. They require a way to help their customers manage the performance of their pumps. We can think of this issue having three parts:

  1. Transforming the nature of maintenance at the client’s customer’s factories, moving from a reactive approach of maintenance to a proactive approach. 
  2. Increasing the visibility of real-time processes and therefore allowing active monitoring and predictive monitoring. 
  3. Creating analytical systems that utilize past trends and historical events to predict maintenance requirements before they become an issue. 

VT’s Solution: We combined our IoT (Internet of Things) solution and implemented it with analytical systems. In doing so, we set up and deployed the cloud services to form the backbone of the project. Installed sensors to monitor the pumps, and built analytical models and systems personalized for the maintenance prediction of the client’s pumps. Integrated the solution with the OSI PI system.

We utilized Enhanced Condition Data Point Monitoring (eCDPM) which combines 24/7 equipment monitoring (via sensors) with traditional route based condition data point monitoring. Full spectrum vibration analysis reports provided maintenance and reliability teams with improvement recommendations that increase mean time between failure (MTBF) & process efficiency while reducing total cost of ownership.

This helps give a clear understanding of your equipment’s remaining life, most likely failure modes and recommended actions so you can respond to adverse equipment conditions before they impact your organization.

Key Points:

  • Achieved client’s business requirements by introducing technologies that monitor their assets and predict maintenance before major issues arise. 
  • Built an end-to-end implementation to monitor the processes as per client’s needs, deploying cloud connected IoT sensors for assets, building the cloud framework to support it gaining real-time visibility for the assets, and created analytical models to provide predictive maintenance capabilities.
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Migrating Data infrastructure into the cloud

Pet-care industry leader with thousands of locations and millions of clients needed to migrate to cloud data infrastructure, requiring a modern data infrastructure from data storage to BI that could utilize advanced analytical techniques to deliver business insights, customer needs and make data-driven business decisions. 

Client: A US-based pet-care, adoption, and grooming services company with thousands of locations.

Problem: The client handles more than 2 million clients per year and provides a broad range of services such as physical exams, vaccinations, surgeries, pet grooming and pet boarding. This leads to a high-volume of data creation which needs to be stored and analyzed. The client was utilizing Microsoft SQL Server, Analysis and reporting services up till now, but they need to modernize this data system and wanted to shift their data systems onto Microsoft Azure, with custom built data lakes connected with Azure Databricks and Azure SQL. In addition, they required personalized analytical and BI systems to be built on top of the data storage. We can think of the business objectives as follows:

  1. Establish the core data infrastructure to be able to answer business questions in a timely manner and deliver Machine Learning driven applications. (Migration to cloud and building analytical models)
  2. Provide actionable insights to business users, enable data driven decision making, by delivering the insights at the right time at the right place. (BI system for business insights)
  3. Provide enterprise level, interactive BI reports & dashboards for various programs such as Home Delivery, Client Reminders, Referral programs and more. (BI system for customer insights)

VT Solution: We provided a migration from Microsoft RDBMS Servers into Azure cloud services, establishing a data lake and connecting it to Azure services such as Databricks and SQL. We built semantic models in Azure Analysis Service for the client’s several business units and business programs. Developing frameworks and designing patterns for data integration into the cloud, moving on-premises data stores into the cloud. Building BI system to build dashboards, visualizations and reports to find business insights and better understand customer needs and demands.

Key Points:

  • Achieved client’s business objectives by establishing a modern data infrastructure on cloud services. 
  • Migrated RDBMS data stores held on client premises to a Azure cloud services
  • Created Data infrastructure including data lakes, analytical models and frameworks, and a modern BI system that fit the client’s data needs
  • Enabled easy to use BI system to allow client’s analytics team to easily access the data and compile reports and stories for enterprise level executives. 
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Letting you do what you do best, and taking care of the rest.

 

Client: A US-based content creation and internet company

Problem: The client has a large library of content that is growing and need to automate the storage and management of the content, while protecting it and being able to scale it as per their requirements. The client has been using legacy data systems and wants to move the service to the cloud. In doing so, they are looking to modernize their data systems, while also shifting some responsibility of the data management onto a managed cloud service. 

VT’s solution: We designed and deployed a custom cloud service meant to form the backbone of the client’s online presence. Migrating the large library of content from the legacy data system onto the newly established cloud. Creating and implementing models that would allow the client to perform analytics over the customer reception and usage of the trends. After implementation, we provided the client with a cost-effective managed cloud service, where we provide cloud security protecting their content, upgrade the systems as new technologies roll in, allowing the client’s online presence to provide the best customer experience. Provided disaster recovery features in cases of emergencies, safeguarding the client’s content, while improving their response time and improving online systems. 

Key Points:

  • Achieved client’s business objectives by migrating and managing their content onto a custom built cloud
  • Provided a reliable solution for the client to maintain their online presence, improving the response times, incorporating security, disaster recovery and analytics at predictable and recurring costs. 
  • Improved customer experience, introduced analytics to allow the client to understand customer trends, allowing them to make data-driven decisions. 
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Strategize to move from the past legacy system to the cloud

Client: A US-based company providing internet services

Problem: The client is one of the most well-known internet service providers. The client collects a high-volume of information on customer data, such as customer browsing trends, financial information, or customer use of service after purchase. The client was using legacy systems in various aspects of their business, however with the increased demand, they were looking for ways to modernize their systems. In the eyes of the client they could expand their on-premises legacy data storage systems or move to a Cloud computing model. The client wanted an in-depth analysis of the costs and savings, highlighting the various opportunities and threats that were involved in both solutions. 

VT’s solution: We started the solution by mapping out the various business processes that exist in our client’s organization, preparing information flow and organizational charts. For the analysis we looked at various ways in which the client’s large data system could be expanded, and how it would compare to different types of Cloud migrations. Given the large scale of the legacy data system and its utility in some departments, it was also important that we provide a strategy that allows for growth, but also integrates some aspects of the legacy systems with it. The solution we presented to our client was a phased migration into the cloud, with integration of the legacy data system as an auxiliary or support system focusing in on a couple of departments. The phased roll out allowed departments to understand the new system as it was rolled out, with gradual modernization that met the clients data needs, and reduced their costs. 

Key points

  • Achieved client’s business objective by providing a cloud strategy from a migration roadmap to analyses focusing on the future growth of the client’s enterprise. 
  • Integrated the legacy data system to maximize savings for our clients, as the legacy systems were built on-premises and could therefore provide support to the modern cloud-based systems without incurring many additional costs. 
  • Showcased multiple strategies for the roll out of the project, highlighting the various aspects of each approach and different ways to integrate and expand the legacy systems in a cost-effective manner. 
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Migrating Data infrastructure into the cloud

Pet-care industry leader with thousands of locations and millions of clients needed to migrate to cloud data infrastructure, requiring a modern data infrastructure from data storage to BI that could utilize advanced analytical techniques to deliver business insights, customer needs and make data-driven business decisions. 

Client: A US-based pet-care, adoption, and grooming services company with thousands of locations.

Problem: The client handles more than 2 million clients per year and provides a broad range of services such as physical exams, vaccinations, surgeries, pet grooming and pet boarding. This leads to a high-volume of data creation which needs to be stored and analyzed. The client was utilizing Microsoft SQL Server, Analysis and reporting services up till now, but they need to modernize this data system and wanted to shift their data systems onto Microsoft Azure, with custom built data lakes connected with Azure Databricks and Azure SQL. In addition, they required personalized analytical and BI systems to be built on top of the data storage. We can think of the business objectives as follows:

  1. Establish the core data infrastructure to be able to answer business questions in a timely manner and deliver Machine Learning driven applications. (Migration to cloud and building analytical models)
  2. Provide actionable insights to business users, enable data driven decision making, by delivering the insights at the right time at the right place. (BI system for business insights)
  3. Provide enterprise level, interactive BI reports & dashboards for various programs such as Home Delivery, Client Reminders, Referral programs and more. (BI system for customer insights)

VT Solution: We provided a migration from Microsoft RDBMS Servers into Azure cloud services, establishing a data lake and connecting it to Azure services such as Databricks and SQL. We built semantic models in Azure Analysis Service for the client’s several business units and business programs. Developing frameworks and designing patterns for data integration into the cloud, moving on-premises data stores into the cloud. Building BI system to build dashboards, visualizations and reports to find business insights and better understand customer needs and demands.

Key Points:

  • Achieved client’s business objectives by establishing a modern data infrastructure on cloud services. 
  • Migrated RDBMS data stores held on client premises to a Azure cloud services
  • Created Data infrastructure including data lakes, analytical models and frameworks, and a modern BI system that fit the client’s data needs
  • Enabled easy to use BI system to allow client’s analytics team to easily access the data and compile reports and stories for enterprise level executives. 
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Modernizing data storage systems using Data lakes

Leader in the chemicals industry needed to streamline data from multiple departments in their organization, so that they could process their high-volume of data and perform real-time analytics for understanding future business needs. 

Client: A global leader in specialty chemical and ingredients distributor based in the US. 

Problem: The client had been working on a legacy data storage platform, which made it challenging to store and analyze data. There were issues relating to data standards amongst the different departments within the enterprise, data duplication and missing data. Due to the legacy data storage platform and the vast amounts of data being collected by the client, they were not able to process the real-time data. The goal therefore was to modernize the data storage platform so that it was more flexible and agile than the traditional data management systems. 

VT Solution: We built an AWS data lake solution for the client so that all data collected throughout the organization can be put together. Improving data accuracy, reducing data redundancy, and forming a single source for all the client’s data needs while also allowing client to traceback to the original data sources. The solution is forward looking as it can be scaled to high data volumes in a cost-effective manner, while also featuring support for different types of analytics. 

These new capabilities allowed our client to generate effective insights by analyzing historical trends and utilizing machine learning models for predictive analytics to get recommendations and forecasts. In addition, it supported future analysis from within the client’s organization, by allowing in-house data analysts, data scientists, and business analysts to access the data using their choice of analytic tools. 

Key Points:

  • Achieved the organization’s goal by designing and implementing a single standard data storage system, reducing data redundancy, and improving accuracy.  
  • Provided a scalable solution that fits the clients need for growth and is personalized to their data requirements.
  • Integrated analytical tools to allow easy access for in-house data professionals and analysts to work on the data with their preference of analytical and BI software.  
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Modern Data Warehousing and Business Intelligence

Multicompany with roots in food supply needed a way to create a data-driven culture within the enterprise, requiring a way to store and utilize their customer, finance, distribution and manufacturing data to make better business decisions.  

Client: A global multicompany known for being one of the largest integrated growers, shippers and packers of multiple fruits, nuts, wines and more. 

Problem: The client was looking to harness the data that they had collected to make better decisions. They were specifically looking to create reports and dashboards to support the Financial, Distribution and Manufacturing divisions. In addition they were looking to find Key Performance Indicators (KPIs) in these business processes to manage their operations efficiently. The client laid out the business objectives as follows:

  1. Nurture a data culture at the client’s enterprise by promoting data-driven decision making, employing data analytics and BI to find actionable insights and future opportunities.
  2. Provide enterprise level, interactive BI reports & dashboards for process areas like Accounting to Reporting, Forecast to Plan, Plan to Procure, Procure to Pay, Order to Cash and more

VT’s solution: To utilize the data gathered by the client, we first needed to build a data warehouse for easy access of data, for which we used Snowflake’s Cloud Data Warehouse. To add structure to the data, we built an automated data ingestion and loading system using Informatica Cloud. After establishing the data source, we created a BI and analytics system, to run data models to find the KPIs for the client and create modern BI reports and dashboards to provide insights and help make data-driven business decisions. 

Key Points: 

  • Achieved client’s business objective by providing the base to build a data-driven culture. By establishing a data warehouse and BI system, we provided the tools necessary for gaining and using data insights to make business decisions.
  • Built a Data Warehouse to allow easy access to data, establishing a single source for all data needs. 
  • Created BI and Analytics system to provide enterprise level, interactive BI reports and dashboards for the various departments in the client’s organization.  
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End-to-End Implementation of BI system

Luxury car maker required a Business Intelligence (BI) system to gain insights about their business processes and gain insights about customer needs and preferences, driving business growth and future opportunities. 

Client: A US-based luxury electric car automaker

Problem: The client had multiple cloud database systems capturing different aspects of the business and the needs and preferences of their customers. They required to bring all the cloud databases into a single data storage solution while also building Business Intelligence (BI) and analytics tools to allow for dashboard and visualization creation. The problem can be thought of has having three parts 

  1. Gather all current data sources into a newly built one data storage system 
  2. Build a foundation for business analytics for various internal departments, so that they can easily get actionable insights and enable data-driven decision making. 
  3. Create enterprise level, interactive BI reports, and dashboards like customer usage reports, customer experience reports or such for the various different departments of the enterprise.

VT Solution: Since the client foresaw a 100x growth with a launch of a new product, one of the requirements was to have a flexible data storage system, that could be scaled rapidly. Therefore, we designed and implemented an AWS data lake to form the basis of data storage system. Bringing in source data from APIs, Legacy RDBMS, SAP, and vehicle files into AWS systems. Building Data Lake, creating data integration and ETL capacities to take raw data from data lake and creating a data warehouse. 

Finally, introducing semantic data models using Power BI to perform analytics, create BI reports and dashboards. Enabled self-service BI for client’s analytics team to utilize the data warehouse and its in-built analytical tools. 

Key Points:

  • Achieved client’s goal by creating an end-to-end implementation of a BI system from the creation of a singular data source, data cleaning, integration, extraction to finally generating BI reports and visualizations
  • Build data lake to form the singular source of raw data throughout the organization, automated data integration and ETL to create a data warehouse. 
  • Built Analytics and BI reporting tools on top of the data storage sources, to allow generation of reports, visualizations, and dashboards for client. 
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