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Data Analytics: Migration to Google Cloud Platform
ABOUT THE CUSTOMER

Our customer is a data analytics company helping businesses quickly onboard to technology tools by crawling the internet for relevant blogs to kickstart a product or technology business.

THE CHALLENGE |

Siloed Data Storage: Transforming data that sits in siloes and is disconnected from the customer experience is challenging, leading to loss of data intelligence for businesses.
Limited Scalability: Scaling a self-hosted application can impact the existing hardware and productivity of your resources.
Higher Upfront Costs: Self-hosting applications require an IT team to install and maintain hardware and software. It takes time and many thousands of dollars.
Reliability Concerns: A downtime would mean that your business is stopped until the issue is resolved, costing you many dollars in productivity and user experience.

THE SOLUTION |

Leveraging CloudifyOps’s comprehensive Cloud Data services enables organizations to get maximum value from their data by eliminating data siloes, reducing financial and resource overheads and simplifying architectures. CloudifyOps’s approach to Data ensures that data is stored, managed, and processed from a central repository, providing all stakeholders with a unified view. This holistic integration enables informed and rapid decision-making process, accelerating the business’s digital transformation journey.

Strategic Outcomes:

  • Unified Data Workflow: Implementation of integrated processes that bring development, security, and operations into a cohesive workflow, enhancing collaboration and efficiency.
  • Consistent and Informed Decision-making: Embedding security practices at every stage of the development process, from initial design to deployment, minimizing vulnerabilities and compliance risks. Operational Excellence involves incorporating operational requirements and feedback early in the development cycle to ensure seamless deployment and reliable performance.
BENEFITS DELIVERED |

Strategic Actions:

  • Real-Time Data Processing: Design and implement a data processing solution to process
    requests in real-time.
  • Tool Integration and Automation: Leveraging state-of-the-art tools that manage and process data quickly and provide a central view to all stakeholders.
  • Cross-functional Training: Providing comprehensive training to customer’s data analytics team.

Key Performance Indicators (KPIs)

  • Data Access and Retrieval: How quickly and efficiently can your team access and retrieve the data is crucial for the business to stay ahead of the competition.
  • Data Consistency: Reduced data input errors and avoiding the need for future rework.
  • Average Database Uptime: Measures the duration of a database staying operational and accessible.
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