Category: Cloud

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. 
Read More