How to Implement SAP Analytics Cloud?

An Exciting and Informative Guide

Onespire Ltd.

SAP Analytics Cloud data visualization tool

Introduction

Several excellent publications have been released on the topic of SAP Analytics Cloud, but few of them examine the potential pitfalls and misunderstandings from the customer’s perspective. I would like to briefly share a few thoughts on this.

What is SAP Analytics Cloud? What are its components?

SAP Analytics Cloud is a data visualization tool that can connect to various types of data sources, import and store their data contents, and visualize them in the form of charts, tables, maps and KPIs, among others.

SAP Analytics Cloud has numerous extremely useful functions, such as being able to organize our data into a tree structure and estimate the results for the next period, which we can then load back into an SAP data source.

In the world of SAP Analytics Cloud, a dashboard could be referred to as a “story”. Widgets visualize the data on the pages of the story. Widgets can be of different types, such as maps, charts, tables, KPIs, value driver trees, etc. A widget is an empty object that needs to be filled with data, which can be done through a model. These are the components of SAP Analytics Cloud.

It is worth carefully planning the pages of the story and the types of widgets, because depending on what we display, we may need multiple models. Nowadays, customers usually purchase an SAP Analytics Cloud subscription for an SAP ERP or Business Warehouse system based on an SAP HANA database. I will explain the significance of this in detail later.

It is important to note that SAP Analytics Cloud is also available on mobile and tablet devices as well, so we can access our latest information anytime.

Where to store our data? What data sources would we like to use to create data visualizations in the SAP Analytics Cloud solution?

It is an important question to consider what data sources we would like to use to build on, because a live data connection can only be established with SAP systems, regardless of whether it is an on-premises or cloud solution. In practice, a live data connection means that when the user opens the story, SAP Analytics Cloud immediately displays the data from the source system.

https://help.sap.com/docs/SAP_ANALYTICS_CLOUD/00f68c2e08b941f081002fd3691d86a7/bdf055159cbb4f36b26c93ccb0c56066.html?locale=en-US

Data modeling should not be performed in the SAP Analytics Cloud! Stories should be built on a solid foundation!

The most important message is that SAP Analytics Cloud is a data visualization tool, not a cloud-based data warehousing solution. Among the business requirements, there is often a story that can be created by filtering, transforming, joining, executing mathematical or statistical operations from numerous large tables or Excel files. SAP Analytics Cloud does not have such advanced modeling capabilities.

It is advisable to perform more complex modeling on the source system’s (SAP ERP or Business Warehouse) side and provide a prepared dataset for visualization. This task is necessary and represents a significant part of the project’s duration. For example, in the case of an SAP BW source system, several views may be the basis of the model, which must be developed one by one. With SAP HANA database and live data connection, it is worth utilizing pushdown capabilities on the source system side to achieve the best performance.

Do not attempt to display millions of data at once in SAP Analytics Cloud!

Consider how much data has to be visualized! It is worth defining filtering parameters on the source side to comply with limitations and achieve optimal performance. The SAP Analytics Cloud requests these parameters when running the story.

Some examples of model and story limitations:

SAP BW, SAP Universe, SAP HANA, Google BigQuery, and SQL data sources: 100,000,000 cells and 100 columns.
For CSV and XLSX, the file size limit is up to 2,000,000,000,000 rows and 100 columns.
Every version of SAP Business Planning and Consolidation (BPC): 2,000,000,000,000 rows and 100 columns.
Google Sheets allows a maximum of 5 million cells, but CSV and XLSX files stored on Google Drive have the same limit as above.
For all other data sources: 800,000,000 rows and 100 columns.

Have a concrete idea and business requirement!

It’s important to have a concrete idea and business requirement of what we would like to see in the story. It’s worth sketching out and drawing what we want to display. With less information, we focus on the most important data and present them in a clear and streamlined form. It’s important that the sketch is complete, when we can determine the exact location of the data behind the widget, the necessary transformations and filters, which, when executed, will give us the expected result.

Who is the story for? Who is the target audience?

Depending on whether a story is intended for executives, team leaders, or users, it can be made up of completely different elements, as their preferences vary. Top executives mainly monitor activities at a strategic level. Managers analyze results at a tactical level. Operational-level colleagues deal with detailed data at a practical level.

Dashboard for strategy: It helps top executives analyze the implementation of the comprehensive corporate and business strategy. It is primarily used for planning and evaluation.

Dashboard for tactics: It helps middle managers to monitor and manage various business processes and projects.

Dashboard for operation: Operational units, stores, factories are supported in their daily, hourly, or other time unit based operations.

Is SAP Analytics Cloud a self-service solution?

Practice suggests that it is naive to think that employees of a large enterprise will create stories on their own. SAP Analytics Cloud is not a complicated tool itself, but serving data requires complex knowledge and skills. In the vast majority of cases, the necessary information is not concentrated in one person’s knowledge but rather in a team’s, as at least three areas of expertise are required:

Knowledge of data: How can data be displayed in a way that speaks for itself? What are the relationships between the data?
Knowledge of source system data modeling: How will the models be served with data? What standard or custom views should be created to serve most stories? How to ensure constraint satisfaction?
Knowledge of SAP Analytics Cloud: How to use the tool? How can I connect it to my systems? Which business content should I use?

Use the standard business content!

SAP provides numerous free business contents that are based on standard objects of the data source (e.g., S4HANA). We can install the content in SAP Analytics Cloud with just a few clicks and test the resulting models and stories with sample data. If we have chosen the right content, putting it into production and customizing it requires further tasks.

https://help.sap.com/doc/ffb5f5ccfbcc437cb5673dc97926c5fd/release/en-US/8919998512534d518ea98297928cb6f1.pdf#page=429

Apply the rules of effective story design!

Define the target audience and plan a story for them!
Show the essence immediately!
Simplify! Avoid using background images and other graphical elements!
Align the elements in a harmonious order!
Highlight the most important information!
Be clear and avoid unfamiliar terms!
Use the company’s branding colors for emphasis!
Leave out unnecessary noise! Let the formatted data dominate in caption-free stories.

What’s the future? Where is SAP Analytics Cloud heading?

The amount of data in the world of smart devices is growing every day. Storing, organizing, and visualizing the collected data plays a crucial role in setting corporate strategies and monitoring activities.

SAP’s strategic goal is to be a leader in the sale of corporate cloud solutions. SAP Analytics Cloud is perfectly compatible with existing on-premises systems, as well as with new cloud ERP (S4HANA Cloud) and data warehouse (SAP Datasphere) solutions, as it provides a seamless transition to the world of stories with just one click.