For the discussion last August 17, the videos were a refresher for everyone. The introduction was apparent and direct to the point.
The first topic, Introduction to Business Analytics, was the term used for the discussion. The video also stated the difference and similarities between Data Science, Business Intelligence, Big Data, Data Mining & Machine Learning. There are a lot of applications for business analytics. It can be for customer relationships, financial marketing, supply chain management, human resource planning, etc. It also discusses the history of business analytics and relates it to a case study.
For those who want to be a business analyst, there are many roles that you can take, such as interpreting data, conducting market analysis, assessing the performance of a business, and helping improve its system. One analyst can be successful only if you have a combination of hard skills and soft skills.
You can also easily use tools, but coding and GUI Programs are separated into two categories. There are SAS, R, Python & SQL for coding, while the GUI Programs are Excel, Tableau, and MS Software. This could make reports and dashboards that can be used for business, stakeholders, or insights.
For the three following videos, it tackles more about how to use some unique features of MS Excel:
The sorting and filtering of data enable users to analyze the results occurring from a given data set. The advantage of using this feature is to make your work easy.
Using Excel formulas will make it easy to perform addition, subtraction, multiplication, and division calculations.
The aggregation is used to obtain information about particular groups based on specific demographic or psychographic variables. It is commonly used in economics and finance.
So far, it was a good refresher since the lesson was taught during the last second year of college during the second semester. It is a much-needed lesson since it will be helpful in this subject.
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