How can you effectively use IBM Watson Analytics for data analysis?

1 Choose a data source

The first step is to choose a data source that you want to analyze with Watson Analytics. You can upload your own data files, connect to cloud services, or use sample data sets provided by IBM. Watson Analytics supports various formats, such as Excel, CSV, JSON, and SPSS. You can also refine your data by applying filters, calculations, aggregations, or transformations.

2 Ask a question

The second step is to ask a question that you want to answer with your data. You can type a natural language query in the search box, such as "What are the factors that affect sales?" or "How does customer satisfaction vary by region?" Watson Analytics will use its cognitive capabilities to understand your question and generate relevant visualizations and insights. You can also explore different aspects of your data by clicking on the suggested topics or keywords.

3 Explore the results

The third step is to explore the results that Watson Analytics provides. You can view different types of charts, tables, maps, or dashboards that show the relationships, patterns, and trends in your data. You can also interact with the visualizations by zooming, filtering, sorting, or drilling down. You can also compare different scenarios, perform what-if analysis, or apply predictive models to your data.

4 Refine the analysis

The fourth step is to refine the analysis that Watson Analytics produces. You can customize the visualizations by changing the colors, fonts, labels, or layouts. You can also add annotations, comments, or notes to explain your findings. You can also modify the queries, filters, or calculations to fine-tune your analysis. You can also create your own visualizations by dragging and dropping the data fields that you want to use.

5 Share the story

The fifth step is to share the story that you create with your data. You can export your analysis as a PDF, PowerPoint, or image file. You can also embed your visualizations in web pages, blogs, or social media platforms. You can also collaborate with others by inviting them to view, comment, or edit your analysis. You can also use the Watson Analytics Storybook feature to create interactive and engaging narratives with your data.

6 Learn and improve

The sixth and final step is to learn and improve your analytical skills and creativity with Watson Analytics. You can access various resources, such as tutorials, videos, blogs, or forums, to learn more about the features and functions of Watson Analytics. You can also provide feedback, suggestions, or questions to the Watson Analytics team to help them improve the platform. You can also challenge yourself by trying new data sets, questions, or scenarios with Watson Analytics.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?