Google Cloud Platform (GCP) offers a wide range of services for data and analytics, so it can be daunting to know where to start. This decision tree can help you narrow down your options and choose the right services for your needs. Then you should ask yourself first:
What type of data do you have?
- Structured data: This is data that is organized in a fixed format, such as rows and columns in a spreadsheet. Examples of structured data include customer records, financial transactions, and product inventory.
- Unstructured data: This is data that is not organized in a fixed format, such as images, videos, and text documents. Examples of unstructured data include social media posts, customer reviews, and medical records.
What are your analytics goals?
- Descriptive analytics: This type of analytics helps you understand what has happened in the past. Examples of descriptive analytics include reporting, trend analysis, and anomaly detection.
- Diagnostic analytics: This type of analytics helps you understand why something happened. Examples of diagnostic analytics include root cause analysis and correlation analysis.
- Predictive analytics: This type of analytics helps you predict what will happen in the future. Examples of predictive analytics include forecasting, churn prediction, and risk scoring.
How to make decisions about managing your data analytics workload and achieving your goals?
- Define your goals. What do you want to achieve with your data analytics workload? Do you want to improve customer satisfaction, increase sales, or reduce costs? Once you know your goals, you can start to make decisions about how to manage your workload.
- Understand your data. What kind of data do you have? How is it structured? Where is it stored? Understanding your data is essential for making informed decisions about how to manage it.
- Choose the right tools. There are a wide variety of tools available for data analytics. Some tools are better suited for certain types of data or for certain goals. Choose the tools that will help you achieve your goals most effectively.
- Build a team. Managing a data analytics workload is a complex task. You need a team of people with the right skills and experience to help you succeed. Build a team that understands your goals and your data, and that can help you make the best decisions for your workload.
- Measure your results. Once you have implemented your decisions, it is important to measure your results. This will help you determine whether your decisions are having the desired impact. You can use the results of your measurements to make further adjustments to your workload as needed.
If you want to make informed decisions about managing your data analytics workload and achieve your goals. For more details, please visit the Google Cloud blog post by Priyanka Vergadia, Staff Developer Advocate, and Alicia Williams, Developer Advocate. They have created an interactive decision tree that provides a clear overview of data and analytics workloads on GCP. The link is below.