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Viewpoint Analytic Platform blueprint A capability checklist for Operational AnalyticsViewpointTable of contents346912141619Translate analytics into results Use a blueprint for Operational Analytics Review

How to fill out an analytic platform blueprint

How to fill out an analytic platform blueprint

1. Step 1: Start by identifying the goals and objectives of the analytic platform blueprint. Determine what data you want to collect and analyze, and what insights you want to gain.
2. Step 2: Choose the right analytic platform that aligns with your business needs and requirements. Consider factors like scalability, performance, security, and ease of use.
3. Step 3: Define the data sources that will feed into the analytic platform. This can include databases, APIs, streaming data sources, and more.
4. Step 4: Design the data model for the analytic platform. Determine how the data will be structured, organized, and related to each other.
5. Step 5: Implement data collection mechanisms to gather the required data. This may involve setting up data connectors, creating data pipelines, or integrating with existing systems.
6. Step 6: Configure the analytic platform to perform the desired analysis. Define the metrics, indicators, and reports that will provide insights into the data.
7. Step 7: Test the analytic platform to ensure it is working as expected. Validate the data accuracy, performance, and functionality of the platform.
8. Step 8: Train users on how to effectively use the analytic platform. Provide them with the necessary tools, documentation, and resources to make the most out of the platform.
9. Step 9: Monitor and maintain the analytic platform on an ongoing basis. Regularly review the data, identify any issues or improvements, and make necessary adjustments.
10. Step 10: Continuously iterate and improve the analytic platform blueprint based on feedback, changing business needs, and technological advancements.

Who needs an analytic platform blueprint?

1. Businesses and organizations that rely heavily on data-driven decisions and insights.
2. Data analysts and data scientists who need a structured and organized platform to analyze and visualize data.
3. Management teams looking for a comprehensive view of their business performance and trends.
4. IT departments responsible for managing and maintaining data analytics infrastructure.
5. Companies involved in industries like finance, marketing, healthcare, e-commerce, and more, where data analysis is crucial for success.
6. Startups and entrepreneurs looking to build a solid foundation for their data analytics capabilities.
7. Researchers and academics who require a platform to analyze and interpret research data.
8. Government agencies and public institutions that need to analyze and track various datasets.
9. Any individual or organization that wants to gain valuable insights from their data and make data-driven decisions.

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