Understanding the Role of Models in SAP Analytics Cloud and How to Create One

By Cindy San

Table of Contents

In the world of data analysis, the term “model” holds significant importance. It’s a crucial concept that empowers businesses to make sense of their data, draw insights, and make informed decisions. In this article, we’ll dive into the concept of a model in SAP Analytics Cloud and understand why creating one to import data is the foundational step for informed decision-making.

Understanding Models in SAP Analytics Cloud

In SAP Analytics Cloud, a model is a structured representation of your business data. It acts as a blueprint that defines how different data points relate to each other. Think of it as a digital canvas where you map out the intricate web of connections within your data. Creating a model allows you to visualize and analyze your data more effectively.

Why Create a Model to Import Data?

Creating a model before importing data might sound like an extra step, but it’s a strategic move that holds the following benefits:

  1. Structured Organization: A model provides a structured framework for your data. It’s like creating different compartments for various types of data, making it easier to navigate and interpret.
  2. Relationship Mapping: Business data is interconnected. Creating a model lets you map out these relationships. For instance, you can link sales data to product data or customer data, revealing insights that might have gone unnoticed otherwise.
  3. Enhanced Analysis: Within your model, you can define measures, which are quantitative metrics representing various aspects of your business. Measures like “Quantity Sold” or “Price” provide actionable insights for decision-making.
  4. Predictive Insights: Models aren’t just about historical data; they can also predict future trends based on patterns. This predictive ability can be a game-changer for your business strategies.
  5. Efficient Decision-Making: With a well-structured model, you can swiftly access the information you need for data-driven decision-making. No more sifting through heaps of unorganized data.
  6. Collaboration and Consistency: A model ensures consistency across your team. Collaboration becomes seamless when everyone follows the same structure, and insights are more coherent.

Creating a Model and Importing Data in SAP Analytics Cloud

Let’s break down the process of creating a model and importing data within SAP Analytics Cloud:

  1. Creating Measures: Start by defining measures for your business data, such as “Price” and “Quantity Sold.” Specify the measurement units and decimal places as needed.
  2. Building the Model: Create a new model within the SAP Analytics Cloud platform. Give it a meaningful name that aligns with your business context. This model will serve as the foundation for your data analysis.
  3. Mapping Relationships: Identify and map relationships between different data elements. For instance, connect “Price” to “Product” and “Quantity Sold” to “Transaction.” This step outlines how your data components interact.
  4. Importing Data: Utilize the data import feature to bring your data into the model. Map the columns in your data source file to the measures you’ve defined. Ensuring accurate mapping is crucial for precise analysis.


The video provides a guide on creating a model and importing data in SAP Analytics Cloud.

In the realm of SAP Analytics Cloud, models are the building blocks of effective data analysis. They provide structure, clarity, and actionable insights from your business data. By creating a model and importing your data into it, you’re embarking on a journey of discovery and informed decision-making.

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