As the project manager of the newly designed system for the oncology department, you are asked to provide a memo for the upcoming meeting with the chief executive officer (CEO) and a few senior managers. They are unaware of the features that have been designed and need a quick refresher prior to implementation. Therefore, you will provide and explain the details of the following:
- Explain the purpose of data analysis, data transformation, and visualization.
- Give an overview of business intelligence and a data warehouse.
- Explain the basics of building tables.
- Explain the use of pivot tables.
- Identify the database to be used.
- Explain the concept of functions and expressions.
The use of APA style is expected.
deliverable length: 2-3 pages
Expert Solution Preview
Introduction: The newly designed system for the oncology department requires a quick refresher on the features that have been designed prior to implementation. As the project manager, you are asked to provide a memo for the upcoming meeting with the CEO and senior managers. The memo should aim to explain the purpose of data analysis, data transformation, and visualization, give an overview of business intelligence and data warehouse, explain the basics of building tables, explain the use of pivot tables, identify the database to be used, and explain the concept of functions and expressions.
1. Explain the purpose of data analysis, data transformation, and visualization.
Data analysis, data transformation, and data visualization are crucial components of any data-driven decision-making process. Data analysis involves gathering, cleaning, and examining data sets to extract meaningful insights and valuable information. Data transformation involves the process of converting data into a different format to make it more accessible, usable, and valuable. Data visualization, on the other hand, involves the use of charts, graphs, and other visual representations to communicate insights in a way that is easy to understand and digest.
2. Give an overview of business intelligence and a data warehouse.
Business intelligence (BI) refers to the practice of leveraging technologies and applications to analyze and process raw data to uncover insights, trends, and patterns that drive better decision-making. BI enables businesses to identify opportunities and threats in real-time and make informed decisions based on data-driven insights. A data warehouse, on the other hand, is a large repository of data that can be accessed and analyzed for BI purposes. It is designed to provide a consolidated view of data from different sources and can be used to support decision-making across various functions in an organization.
3. Explain the basics of building tables.
Tables are basic components of any database and are used to store data in columns and rows. To build a table, you need to define the columns and their data types, and then populate it with data. Each column should be given a meaningful name, data type, and size. Tables must have a primary key that uniquely identifies each row in the table. Indexes must also be created to improve the performance of database queries.
4. Explain the use of pivot tables.
A pivot table is an interactive table that enables users to summarize and analyze large volumes of data quickly. Pivot tables allow users to group, filter, and summarize data in various ways, making it easier to gain insights and identify trends over time. Pivot tables are highly customizable and can be used to generate charts and graphs that visualize data trends.
5. Identify the database to be used.
The database to be used should be a highly reliable and scalable database that can handle large volumes of data. One option is Oracle database, which is known for its high availability, scalability, and performance. Another option is Microsoft SQL Server, which provides a wide range of data management tools and support for advanced analytics and reporting.
6. Explain the concept of functions and expressions.
Functions and expressions are used to manipulate data and generate insights. Functions are predefined formulas that perform specific operations on data, such as calculating averages or summing values. Expressions, on the other hand, are user-defined formulas that enable users to customize data analysis and generate custom insights. They can be used to perform complex calculations, concatenate string values, and more.
