1- What is the new programming language for business intelligence? Discuss the rationale behind Python. Length: 10 sentences. Word document. ———————————————————————— 2- A program uses a char variable named department and two double variables named salary and raise. The department variable contains one of the following letters (entered in either uppercase or lowercase): A, B, C, or D. Employees in departments A and B are receiving a 2% raise. Employees in department C are receiving a 1.5% raise, and employees in department D are receiving a 3% raise. Using the switch statement, write the C++ code to calculate the appropriate raise amount. SAVE AS homework3.cpp ——————————————————————— 3- Modify the solution shown earlier in Figure 7-2( SEE ATTACHED BELOW). The solution should now keep track of the number of times Sahirah’s laser beam missed the spider. After saying “You are safe now. The spider is dead.”, Sahirah should say one of the following: “I got him  immediately.”, “I missed him one time.”, or “I missed him x times.” (where x is the value in the counter). FIGURE 7-2 IS ATTACHED. SAVE AS homework-3.cpp

The new programming language for business intelligence that has gained significant popularity and recognition is Python. The rationale behind the choice of Python for business intelligence can be attributed to several factors.

Firstly, Python is known for its simplicity and ease of use. It has a straightforward syntax and requires less code compared to other programming languages. This makes it easier for analysts and data scientists to quickly prototype and develop business intelligence applications.

Secondly, Python has a vast ecosystem of libraries and frameworks that are specifically designed for data analysis and visualization. One of the most popular libraries in this regard is Pandas, which provides high-performance data manipulation and analysis tools. Additionally, libraries such as NumPy and Matplotlib allow for efficient numerical computations and data visualization, respectively.

Furthermore, Python has strong support for machine learning and artificial intelligence, which are key components of modern business intelligence systems. Libraries like Scikit-learn, TensorFlow, and PyTorch enable developers to implement complex machine learning algorithms and models with ease.

Another advantage of Python is its cross-platform compatibility. It can run on various operating systems such as Windows, macOS, and Linux, making it highly flexible and accessible for business intelligence professionals.

Python also benefits from a vibrant and active community of developers and users. This means that there are a wealth of online resources, forums, and user-contributed libraries available, which facilitates knowledge sharing and collaborative problem-solving.

Moreover, Python integrates well with other data management and analytics tools commonly used in the business intelligence field. It can easily connect to databases such as SQL or NoSQL databases, as well as integrate with big data processing frameworks like Apache Spark.

In terms of performance, Python may not be as fast as some low-level programming languages like C or C++. However, advancements such as the JIT (Just-In-Time) compilation provided by libraries like Numba and the ability to utilize distributed computing frameworks can mitigate this limitation to a certain extent.

Overall, the rationale behind choosing Python as the new programming language for business intelligence stems from its simplicity, extensive library ecosystem, support for machine learning, cross-platform compatibility, strong community, and seamless integration with other data management tools. These factors make Python a powerful and versatile language for developing sophisticated business intelligence applications.

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