How to Setup SAP BTP Trial Account and Create SAP HANA Cloud Database

How to Setup SAP BTP Trial Account and Create SAP HANA Cloud Database

In this blog, we will register account in sap.com and then we will setup SAP HANA BTP trial account.

Create login in sap.com

You have to register in sap.com. You have to provide business email, first name, last name etc... You can select department and relationship to SAP according to your job profile. I have selected "Administrator" as department and Relationship to SAP as "Student".

https://www.sap.com/

After registration, next screen will get to check email.

In email, you will link to activate your account. You have to click that link.

Next screen will come like below. Need to create password and check the both acknowledge then click "Submit".

Next screen will show like below:

Login to SAP BTP Cockpit to create trial account

After login go to SAP BTP Trial page. For that you have to go to below url: https://cockpit.hanatrial.ondemand.com/trial/#/home/trial. First time it will ask you to verify your telephone number. You have to enter your phone number, immediately you will get verification code. That code you have to enter and press "Continue".

Next screen will ask to accept Terms and Conditions, click the checkbox and click "Accept".

In next screen it will ask to choose the region for trail account. I have selected US East(VA) - AWS. Then click "Create Account".

Next screen will show like below.It is creating a trial account. It will take some time to create.

After some time, you will get screen like below. Then click on "Continue".

Next screen will show like below. Click on "Go To Your Trial Account".

Next screen will show like below:

Scroll down, you will see trial under Subaccounts. Click on "trial".

Next screen show like below.

On the same page, you will see dev. Click on "Dev".

Next screen will show like below. Click on "SAP HANA Cloud".

Click on "Create".

Choose SAP HANA database.

It will ask you to choose your identity provider. You have to click on "Sign in with default identity provider".

Click on "Accept" for Legal Disclaimers

Next screen will display like below. Click on "SAP HANA Cloud, SAP HANA Database".

Next will show like below:

Location and Space are already selected. No need to change right now. We have to provide database instance name, administrator password and confirm administrator password. User is DBADMIN. Then click on "Next Step."

Default memory size is 30GB and storage is 120GB. No need to change. Click on "Create Now".

Next screen will show the details of SAP HANA Cloud. Click on "Create Instance".

Make sure you allow all IP addresses.

Next screen will show like below:

Go to previous screen, you will see SAP HANA Database instance is "creating in progress".

It will take some time to create. After some time, you can see database instance created.

SAP HANA Database Instance created. Let us Open in SAP HANA Cockpit. Click on Actions -> Open In SAP HANA Cockpit.

In next screen, it will ask you to enter database username and password. Then click on "OK".

Next screen will show like below. Database is running status. We can see database user and host also.

Manage SAP HANA Cloud

If we are not working with SAP HANA Cloud Database, we can stop and later we can start. Click on "Manage SAP HANA Cloud".

Then You have to click on "Sign in with default identity provider". Then next screen will show like below

Click on three dots on SAP HANA Cloud Database Instance.

Click on Stop.

Next screen will come like below, then click on "Stop".

After that we can see it is stopping the database instance.

After some times, we can see it in "STOPPED" status.

That's it in blog. In next section, we will open database instance in SAP HANA Database Explorer. We will create schema and table and insert data into that table. After that we will connect SAP HANA Cloud Database with Python.

In [ ]:
 

Machine Learning

  1. Deal Banking Marketing Campaign Dataset With Machine Learning

TensorFlow

  1. Difference Between Scalar, Vector, Matrix and Tensor
  2. TensorFlow Deep Learning Model With IRIS Dataset
  3. Sequence to Sequence Learning With Neural Networks To Perform Number Addition
  4. Image Classification Model MobileNet V2 from TensorFlow Hub
  5. Step by Step Intent Recognition With BERT
  6. Sentiment Analysis for Hotel Reviews With NLTK and Keras
  7. Simple Sequence Prediction With LSTM
  8. Image Classification With ResNet50 Model
  9. Predict Amazon Inc Stock Price with Machine Learning
  10. Predict Diabetes With Machine Learning Algorithms
  11. TensorFlow Build Custom Convolutional Neural Network With MNIST Dataset
  12. Deal Banking Marketing Campaign Dataset With Machine Learning

PySpark

  1. How to Parallelize and Distribute Collection in PySpark
  2. Role of StringIndexer and Pipelines in PySpark ML Feature - Part 1
  3. Role of OneHotEncoder and Pipelines in PySpark ML Feature - Part 2
  4. Feature Transformer VectorAssembler in PySpark ML Feature - Part 3
  5. Logistic Regression in PySpark (ML Feature) with Breast Cancer Data Set

PyTorch

  1. Build the Neural Network with PyTorch
  2. Image Classification with PyTorch
  3. Twitter Sentiment Classification In PyTorch
  4. Training an Image Classifier in Pytorch

Natural Language Processing

  1. Spelling Correction Of The Text Data In Natural Language Processing
  2. Handling Text For Machine Learning
  3. Extracting Text From PDF File in Python Using PyPDF2
  4. How to Collect Data Using Twitter API V2 For Natural Language Processing
  5. Converting Text to Features in Natural Language Processing
  6. Extract A Noun Phrase For A Sentence In Natural Language Processing