In a previous article, we shared the processes and roadmap for business intelligence. Now, Business intelligence tools. in connection with another article, I’m leaving you alone.
There are many benefits to knowing Excel, SQL, and Python programs to become a business intelligence expert. These programs help business intelligence professionals collect, clean, analyze, and report data. Excel is a powerful tool for business intelligence professionals to organize, analyze, and visualize data. Excel provides various data visualization tools like tables, charts, and pivot tables. These tools help business intelligence professionals understand data more easily and extract meaningful insights. SQL is a programming language used to extract and manage data from databases. Business intelligence professionals can use SQL to fetch, join, and analyze data from databases, allowing them to conduct more comprehensive and accurate analyses. Python is a general-purpose programming language that business intelligence professionals can use for data collection, cleaning, analysis, and reporting. Python is a fast and efficient language that helps business intelligence professionals tackle complex tasks with ease. Knowing Excel, SQL, and Python programs is a crucial step towards a successful career in business intelligence. These programs enable more efficient and effective work with data in the field of business intelligence. Here are the benefits of learning these programs:
Excel
- Power BI, Tableau, Qlik Sense, and other business intelligence tools incorporate many of Excel’s functions. However, having a good grasp of Excel can help you use these business intelligence tools more efficiently. Here’s why you should be proficient in Excel for business intelligence tools:
- Data organization: Excel’s data organization tools can help you quickly and easily manage data. This simplifies data analysis in business intelligence tools.
- Data analysis: Excel’s data analysis tools can facilitate data analysis in business intelligence tools. This helps you extract more meaningful insights from data.
- Data visualization: Excel’s data visualization tools make it easier to create clear and engaging visualizations. This makes your data more understandable. Here are some specific advantages of being proficient in Excel for business intelligence tools:
- Reduces data analysis time. Using Excel’s data organization and analysis tools, you can analyze data more quickly, making data analysis in business intelligence tools more efficient.
- Enhances the effectiveness of data visualizations. Using Excel’s data visualization tools, you can present your data in a more understandable and compelling way. This makes data visualization in business intelligence tools more effective.
- Simplifies complex tasks. Excel is a powerful tool for business intelligence tools. Being proficient in Excel makes it easier to complete complex tasks in business intelligence tools. In conclusion, being proficient in Excel can help you use business intelligence tools more efficiently and effectively, leading to success in your career.
SQL Query Operations
- SQL Query Operations Business intelligence tools often provide SQL query support, allowing business intelligence professionals to directly analyze data from databases. Having SQL query skills enables business intelligence professionals to use business intelligence tools more efficiently and effectively. For example, in Power BI, a business intelligence query language like DAX allows you to perform various operations. Knowing the SQL query language is beneficial for using DAX and simplifying your work. For instance, if you’ve created a measure for the total sales amount, you can use it in all related charts and tables. Here are some specific examples of what you can do with Power BI DAX, which is a query language for business intelligence:
- You can use DAX to group sales amounts by product in a sales report. This helps you understand how sales perform for specific products.
- In a production report, you can use DAX to divide production costs by the production quantity. This helps you calculate the unit production cost.
- In a marketing report, you can use DAX to filter website traffic for a specific date range. This helps you understand how your website performs during a particular period.
- The same applies to other business intelligence tools.
Python
Python is an important tool for becoming a business intelligence expert. Python is a general-purpose programming language that can be used for data collection, cleaning, analysis, and reporting. The significance of Python for business intelligence includes:
- Data collection: Python can be used to collect data from various sources, including websites, databases, and even physical devices.
- Data cleaning: Python can be used to clean and preprocess data, ensuring it’s consistent and accurate.
- Data analysis: Python offers various statistical and analytical tools for data analysis. Python is particularly important for big data. Python’s relevance for big data includes:
- Performance: Python is fast and efficient, making it suitable for processing large datasets.
- Accessibility: Python is easy to learn and use, making it popular among big data analysts and data scientists.
- Features: Python provides a wide range of features and tools necessary for big data analysis. Please let me know if you need any further assistance or if you’d like me to elaborate on any specific aspect.”
AHMET GÜNOĞLU
ERP Consultant and Business Intelligence Expert
https://www.ahmetgunoglu.com/blog
https://medium.com/@ahmetgunnnnn