Configuring SAP Analytics Cloud System

1. SAP Analytics Cloud (SAC): A cloud-based data visualization and analytics platform that integrates with other SAP products to enable data analysis and reporting.
2. HANA Database Explorer: A tool for managing HANA Databases, allowing for the setup and configuration necessary to align with SAP Asset Performance Management.
3. Live Connection: A direct link established between SAP HANA Cloud and SAP Analytics Cloud that enables real-time data access and manipulation.
4. Model: In SAC, a representation of the data that has been structured and defined for analysis, often based on calculation views created in the HANA database.
5. Story: A feature in SAC where data and visualizations are grouped together to present information on a specific topic, often for reporting purposes.
6. Modeler Page: The interface in SAC where users create and define new data models for analysis.
7. Measures: In data modeling, these are quantifiable metrics derived from dimension values, used for analysis in a model.
8. All Dimensions Tab: Part of the model creation process in SAC that displays all table columns, allowing for additional descriptions, hiding dimensions, or grouping.
9. Calculation Views: Configurations within SAP HANA that allow for the manipulation and transformation of table data using SQL operators, clauses, and functions.
10. User Provided Service (UPS): A service in SAP that allows for the provisioning of credentials to a remote resource, such as the HANA Database Explorer.
11. HANA Database Project: A project set up within Business Application Studio to create calculation views that will be used within SAP APM.
12. hdbgrants File: A configuration file that specifies the privileges of database owners and users, defining who can access and manage the database.
13. Canvas Story: A type of story in SAC optimized for a more free-form layout, allowing for a variety of visualizations and textual elements.
14. Technical User: A user role with specific privileges, often used for back-end connections between systems and databases.
15. Data Visualization: The graphical representation of data within SAC to facilitate easy understanding and analysis of complex datasets.

In this lesson, Jessica will learn how to tailor SAP Analytics Cloud System to work in concert with SAP Asset Performance Management, ensuring that CRT Manufacturing can conduct thorough data analysis and reporting for improved asset oversight.

 SAP Analytics Cloud (SAC) is a data visualization tool that allows you to connect data with it from another SAP products. What we are going to do here is connect the data from our SAP HANA Database Explorer with SAP Analytics Cloud. From there, we will create a model, which is some representation of the data we have and want to visualize. Once we have a model, we can go ahead and create a story, which is essentially a grouping of data and visualizations all relating to a particular topic.

Open your SAC tenant. On the main page of SAC, choose on the Burger icon on the left sidebar (three horizontal lines) to expand it. Towards the bottom of the sidebar, choose on the Connections button to set up the initial connection between SAC and SAP HANA Cloud.

Choose on the + icon at the top of the page to add a connection.

Choose on the Connect to Live Data dropdown and choose on the SAP HANA option from there.

Set a name for the connection here. Use the dropdown for the Connection Type and chose SAP HANA Cloud.

For the Host field, this will be found via SAP HANA Cloud Central. Locate the HANA Instance you are using to run HANA Database Explorer and choose the icon with the three dots under the Actions column.

Choose Copy SQL Endpoint to receive the host field.

Choose Copy SQL Endpoint to receive the host field.

When you paste the SQL Endpoint to the Connection pop up in SAC, a colon (:) as well as the port number are included, make sure to delete these from the Host field.

Keep the Authentication Method as User Name and Password. Use the user and password that we created within HANA Database Explorer who we granted the roles to for accessing our calculation views. Once the User Name and Password are entered, choose the OK button at the bottom left of the pop up.

Keep the Authentication Method as User Name and Password. Use the user and password that we created within HANA Database Explorer who we granted the roles to for accessing our calculation views. Once the User Name and Password are entered, choose the OK button at the bottom left of the pop-up.

Once the Connection is made, we can see it on the Connections page. We will now create the model based on the calculation views that were created within BAS and deployed into HANA Database Explorer. Use the left side bar and navigate to the Modeler page to create the new data model.

On the Modeler Page, choose the Live Data Model button in the Create New section of the page.

In the pop up, select the System Type as SAP HANA. For the Connection, choose the name of the Live Connection we just created. Choose the overlapping square icon for the Data Source to select which Data Source will be used for the model here.

The list of data sources that can be accessed by this model will appear. In our scenario, we are going to see all the calculation views that are a part of our hdi container that we have authorization to access from our newly created user within HANA Database Explorer. Choose the calculation view you want to make a model from.

Choose the OK button once all fields are filled in.

The newly generated model will open to the Measures tab. Measures are calculated data taken from the dimension values. The dimensions are the fields that we added in as a part of our calculation views. We can choose a spot somewhere in the cells for the different measures here to provide additional values in which we would go and define them. For now, we are not going to concern ourselves with the measures here. We will be doing similar work when we actually create the story. Switch to the All Dimensions tab located next to the Measures tab once finished.

In the All Dimensions tab, we see the table columns that we added to our mapping when we created the calculation view. We can add an optional description, hide the dimensions from the model, or group the dimensions by associating them with a group name. We will leave all this information as is though. Once finished, choose on the save icon near the top of the page to save the model.

Enter a name and an optional description for the model. We can also specify a location to save the model to as well. Once finished, choose the Save button at the bottom right of the pop up to save the model.

The model has now been successfully saved. A pop up will appear on the bottom of the screen indicating this. Now go to the side bar on the left and choose the Stories button to go ahead and create a new story for our model.

One the Stories page, the story that we will be creating is a Canvas story. Choose the Canvas button on the Stories page.

If prompted with a Design Mode Type, select the Optimized Design Experience. Choose the Create button at the bottom right of the pop up once finished.

We will need to add the data from our model to story so we can utilize it in here. On the left section of the page, choosen the Add data button to link our model to our story.

There are three options on where to choose to obtain the data from. Choose the bottom option, Data from an existing dataset or model.

Navigate through the file structure to locate the model that you will be using for the story. Choose on the model to add it once found.

Now the model is added to our story. From here, we will choose a data visualization for us to create. The one that we are going to create here is a Chart. Choose the Chart button on the right half of the page.

Inside the story, you will have many different data visualization options to choose from and implement. Much of how you would go about implementing your story is up to you and as determined on what the data is that you are implementing here. I will show off how to make a basic story based off the information in the model that I've made here, but this is far from an extensive showcase of the features of SAC stories. Do not feel obligated to strictly follow along with the story here.

If working with a chart, it will default to a bar/column graph. We are going to need at least one measure though for our chart to map out. Measures in a chart are the qualitative data containing numerical data. In the Designer tab on the right of the page, choose the + button in the Measures section to add a measure to your chart.

Check off the Measures you will be using for the chart, you can add additional calculations or Measure Input Controls as well.

Now we can add dimensions to our chart. Dimensions contain more of the qualitative data that describes the numerical dimension data. Choose the + button in the Dimensions section of the char builder to add in dimensions.

Check off the dimensions you wish to use here.

A simple bar graph has been created now. We can also add additional data in here as well. I added a donut chart to mine as well with some separate information. Again, please make your own story as you see fit.

We can also add in information that is strictly for displaying data. We can add in more static elements to our story such as images, text, shapes, and so on. In the Insert Section, choose the + dropdown and select a static element such as Text.

Once you add the text box, give it some text. You can also stylize the text or the text box too. Play around with these options as you see fit.

Once finished with your story, navigate to the file section of the sub header bar at the top of the page. Choose the Save icon to save your story.

Choose a location to save the story as well as provide a name to the story as well. A description can optionally be entered as well. Choose the OK button at the bottom right of the pop up to finish saving your story.

A green text field at the bottom of the page will indicate whether a story has successfully been saved. If you see it, you should be good to go.

Enabling the Analytics Infrastructure for Custom Capabilities

https://help.sap.com/docs/SAP_APM/1bb12075258a41e1a024d28a6ddfe246/b4b93cc500af45ba84d851bd84ffb9f1.html

Reflect on a time when you had to gather and interpret complex data to make an informed decision. Consider the steps involved in that process.

How do you think the integration of tools like SAP Analytics Cloud and HANA Database Explorer could have streamlined your analysis and enhanced the outcome?

Expert Response to Personal Reflection Question:

Utilizing SAP Analytics Cloud (SAC) and HANA Database Explorer in your decision-making process could have streamlined your data analysis significantly. With live data connections, SAC enables immediate access to the latest information, avoiding delays inherent in manual data gathering. The visualization capabilities of SAC can turn complex datasets into clear, interactive charts, making trends and patterns easier to spot and understand.

Had these tools been available in your past experiences, you would likely have seen quicker decision-making, enhanced team collaboration through shared visual insights, and a stronger confidence in the outcomes due to the up-to-date and reliable data. In essence, these SAP tools could have provided a more efficient, accurate, and responsive approach to handling complex data for informed decisions.

Overview: SAP Analytics Cloud (SAC) is a powerful data visualization tool enabling users to connect data from various SAP products. In this lesson, we focus on establishing a live connection between SAP HANA Database Explorer and SAC, creating a data model, and generating a compelling story based on the connected data.

Connection Setup:

1. Open SAC tenant, access the sidebar, and choose Connections at the bottom.
2. Add a live connection by selecting SAP HANA from the Connect to Live Data dropdown.
3. Configure the connection details: Name, SAP HANA Cloud as Connection Type, and provide the Host obtained from HANA Cloud Central.
4. Use User Name and Password authentication with credentials from HANA Database Explorer.
5. Save the connection.

Model Creation:

1. Navigate to the Modeler page from the left sidebar.
2. Choose Live Data Model in the Create New section.
3. Choose SAP HANA as System Type and select the live connection.
4. Pick a data source (calculation view) and save the model.
5. Customize measures and dimensions if necessary.
6. Save the model with a name and optional description.

Story Creation:

1. Go to the Stories page, choose Canvas story, and select Optimized Design Experience.
2. Link the model to the story by choosing Add data and choosing the existing dataset or model.
3. Select the model and add it to the story.
4. Choose a data visualization type (for example, Chart) for your story.
5. Customize the chart with measures and dimensions, adding additional visualizations as desired.
6. Enhance the story by incorporating static elements like text, images, or shapes from the Insert Section.
7. Save the story, providing a name, location, and optional description.
8. Confirm successful saving indicated by a green text field at the bottom.