Python IDLE vs. SAP HANA Cloud

Scenarios where python IDLE is well suited 1-Quick scripting and prototyping 2-Education and training 3-small projects utilities 4-exploring python libraries and modules Scenarios where python is less appropriate 1 large scale projects 2 complex debugging and profiling 3 multi language development 4 Advanced code analysis and inspection

I think if you have a large organization, it's probably the product and the marketplace to go to. We're a large management consulting firm operating in four to seven countries. And generally speaking, I think that's the size and the scope where it scales best. I can't speak to smaller companies, but I can't see smaller companies leveraging the benefits as much as a larger organization can.

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• Firstly, I would say Python IDLE interface is user friendly.
• Easy to learn for the beginners.
• Syntax highlighting is nice features.
• Smart indent helps a lot.

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• Real-time reporting and analytics on data: because of its in-memory architecture, it is perfect for businesses that need to make quick decisions based on current information.
• Managing workload with complex data: it can handle a vast range of data types, including relational, documental, geospatial, graph, vector, and time series data.
• Developing and deploying intelligent data applications: it provides various tools for such applications and can be used for machine learning and artificial intelligence to automate tasks, gain insights from data, and make predictions.

• Too simplistic
• Could not find source revision management integration support
• Only basic debugging is available
• Does not have data-science-specific notebooks (but can be installed separately)

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• Requires higher processing power, otherwise it won't fly. How ever computing costs are lower. Incase you are migrating to cloud please do not select the highest config available in that series . Upgrading it later against a reserved instance can cost you dearly with a series change
• Lack of clarity on licensing is one major challenge
• Unless S/4 with additional features are enabled mere migration HANA DB is not a rewarding journey. Power is in S/4

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We would rate our likelihood of renewing at 9/10. SAP HANA Cloud has proven to be a highly reliable and scalable data platform that consistently delivers strong performance. Its seamless integration with our overall SAP landscape, combined with improved analytics and real-time data capabilities, makes it a core part of our long-term technology strategy.

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The IDE Python IDLE is a good place to start as it helps you become familiar with the way Python works and understand its syntax.

This IDE allows you to configure the environment, font, size, colors, .....

It also looks like any simple text editor for any operating system, I work with Windows or Linux interchangeably, and you don't have to learn to use the IDE before programming.

Once the IDE is executed you can start programming directly in it.

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It is very useful solution which provides you speedier data processing, real-time analytics. It helps you manage diverse data types. It also offers you excellent disaster management. It has user friendly interface which helps you navigate system and transactions easily and perform task smoothly.

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so far, we didn't get any outage

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so far good

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Python IDLE support is what the community can give you. As it is free software, it does not have support provided by the manufacturer or by third-parties.

In any case, for most of the problems that normal users can find, the solution, or alternatives, can be found quickly online.

As this IDE is made in Python, the support is the same group of Python developers.

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However, I am not the right person to answer this as we have another department to handle support and contact the service provider for any support required. Although i will say that they are the quick respondent and knows how to handle querry of the customers and provide quick and better support.

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Professional GIS people are some of the most risk-averse there are, and it's difficult to get them to move to HANA in one step. Start with small projects building to 80% use of HANA spatial over time.

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It's easy to set up and run quick analysis in Python IDLE on my local machine. The output is direct and easy to read. But sometimes I prefer Jupyter Notebook when the datasets are large, since it would take too long to run on my local machine. It is easier to run Jupyter Notebook on my cloud desktop

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I have deep knowledge of other disk based DBMSs. They are venerable technology, but the attempts to extend them to current architectures belie the fact they are built on 40 year old technology. There are some good columnar in-memory databases but they lack the completeness of capability present in the HANA platform.

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I don't have visibility in licensing

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Limitation of training deliverable by organization

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We are still in process for the first applciaiton

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• In a short time, we were able to develop several ML models for various teams to make accurate decisions.
• Beginners can easily understand and adapt to GUI.
• We could automate several manual validation tasks and so could reduce human intervention.

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• ROI has always been high in terms of the functionality that it offers and the security features it comes with.
• Managing large volumes of data in real-time is not an easy task, but it does it pretty well with faster data processing.

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