SAP Analytics Cloud (SAC)- Training for Dashboard & Planning

In this course we will discuss about Analytics Cloud in SAP S/4 Hana - SAC

What you'll learn
- SAP Analytics Cloud
- Data Wragling
- Dashboard Preparation
- Cloud Connection

Requirements
- SAP S4 Hana Understanding

Description
SAP Analytics Cloudbrings together analytics and planning in a single solution in the cloud. You can instantly move from insight to action, simulate any scenario for better business outcomes, and generate plans from predictions automatically to drive agile decisions.

SAP Analytics Cloudallows people from throughout an organization to use the company's analytics capabilities. The application's native language functionality makes it simple for users of all levels to gain rapid insights and better decision-making.

The learning journey is geared towards the business user, so you don't need to be a data scientist to successfully use augmented analytics in SAP Analytics Cloud. In fact, you don't need any prior AI or machine learning knowledge andit's easy to understand!

Data Preparation and Wrangling (Datasets and Models)

Learn how to prepare, enhance, and optimize your data using SAP Analytics Cloud with advanced data wrangling and data preparation workflows for both datasets and models.

Choose Between Datasets and Models

Depending of your business case, you can choose between preparing your data using a model or a dataset.

Before building your story, you need to make sure that your data is prepared for scenario analysis. With SAP Analytics Cloud’s wrangling experience, data preparation can be done using either dataset or a model.

They both offer the same level of functionalities and don’t impact the way the data is consumed in stories. However, the way you create and manage these data objects are different, as they address different purposes.

Identify Which Format Fits Best Your Needs

Datasets store data in a single table, and the semantic structure is defined by the metadata. Go for a dataset if you’re only looking to upload data, using a .csv or .xlsx file, and analyze it in a story straight away.

Models store data as a star schema, and the structure of the model is reflected in the database. Go for a model if the structure of the data is already set, or if you already have a structure in mind before importing the data to fit into the model. A model is preferred when it comes to govern the data processing, like in case of planning.

Advantages of Using a Model

Models guarantee that the data they hold follows a series of business rules that certify that workflows such as planning can be run. Changes made to the structure of the model can be done either at the structure level, if the fact table is empty, or by rebuilding the model from the original data preparation session.

Models also support row-level security, fine-grained data management of dimensions, and fact tables.

Advantages of Using a Dataset

Datasets are reactive to change, any modifications you make to the data or data structure are done simply by editing the dataset, without data loss or restriction.

About Datasets and Dataset Types

A dataset is a simple collection of data, usually presented in a table. You can use a dataset as the basis for your story, and as a data source for Smart Predict.

Dataset are first choice when you want to create story/ visualization quickly and do not want to get into structure definition, during data processing or when development do not demand IT governance. In SAP Analytics Cloud, you can encounter different types of datasets:

Standalone Datasets

This type of dataset is stored in SAP Analytics Cloud and you can find it in a folder location (for example, public, private, or workspace) on theFilespage. You create them collecting your data either by importing a data file or collecting files from other systems.

Who this course is for:
- SAP S4 Hana Consultant
More Info