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Starts 3 June 2025 06:29

Ends 3 June 2025

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Case Study: Financial Analysis in KNIME

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.
via DataCamp

120 Courses


3 hours

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Intermediate

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Overview

This case study dives deep into the practical use of KNIME for financial analysis, utilizing real-world purchase data to demonstrate this tool's power. Participants will start with a typical business case that requires detailed financial scrutiny.

The course meticulously guides students through the initial steps of importing Excel, CSV, and SQL data into KNIME, highlighting how to effectively clean and preprocess the data for analysis. This foundational knowledge is crucial for leveraging KNIME for business intelligence and data analysis projects.

Syllabus

  • Answering a business case with KNIME
  • In this first chapter, you'll be introduced to the business case you need to answer and you will plan your KNIME workflow. You will then start building your workflow, beginning with importing the data.
  • Manipulating the data into shape
  • Chapter 2 is where you'll be applying your data cleaning and transformation skills to the London Fire Brigade data. You'll be getting it clean, useful and consistent to make sure that it is suitable for answering the business case. You'll also be practicing the use of metanodes to make the workflow easy to use.
  • Bringing it all together
  • Chapter 3 gives you the opportunity to practice your KNIME merging and aggregation skills to the London Fire Brigade data. You will extract the results that answer the business case. You will be practicing grouping and pivoting to achieve the desired results.
  • Seeing the results
  • Our final chapter practices KNIME data visualization and exporting. You will be creating useful charts and other visualizations to explore the data and sending the data to spreadsheets and databases. The business case will be answered and your first financial analysis project with KNIME will be complete.

Taught by

Andrew Logan


Subjects

Data Science