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Pragmatic Data
Providing the best resources, courses, tools and thought-leading principles in the world of data science
Why do over 80% of data science projects fail??
Frequently this happens because data science projects launch without a clear understanding of the business problem they intend to solve using data. Hypotheses are left untested, and data available is not cleaned and refined.
That’s why Pragmatic Institute developed an approach not just for data analysis, but for businesses to define a problem and solve it with data—tackling problems that are actually going to be tangible and add value within the business.
The Pragmatic Data Insights Model features five phases: Define, Prepare, Refine, Analyze, and Present. Every phase in the model plays a key role in aligning data teams and business leaders to define a question of tangible impact to the business and solve it with the data available.
?? Download the four eBooks diving into each of the phases in the model available today and keep an eye out for the last eBook in the series in the upcoming months.
?? Define: Focus on the specific business problem you want to solve with data
What’s the difference between a successful data analysis project and one that falls flat? Before you begin working with the data, you need to understand what you’re solving for. Discover the most vital questions to ask before embarking on a data analysis project in our in-depth guide.
?? Prepare: Explore the available data and the most useful methods
On average, data practitioners spend 80% of their time preparing and cleaning the data for analysis. However, without data preparation, any subsequent data analysis will be flawed. In this eBook, learn how to put the right data preparation in place and avoid common pitfalls in data projects.
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?? Refine: Revise questions and expectations as necessary
To deliver results for stakeholders and organizations, data practitioners must ensure a project is set up for success before committing the time, labor and resources required for analysis. In this eBook, learn the importance of refining your data project early and having difficult conversations with the project stakeholders based on the feasibility of the project.
?? Analyze: Build models to find actionable insights
It's important for data practitioners to analyze the data at hand with the goal of providing actionable insights and concrete next steps for stakeholders to make data-driven decisions. In this eBook, learn how to simplify your findings into a business strategy that can be easily interpreted and put into action.
Ready to enhance your skills in data analysis and become a strategic contributor to your organization?
Enroll in Business-Driven Data Analysis to move beyond the spreadsheet, deliver actionable insights, and ensure alignment with stakeholders.