--I've completed this for you as a placeholder. Replace this with your query.
--SQL code in this block
SELECT Products.ProductName, od.Quantity
FROM Products
INNER JOIN "Order Details" AS od
ON Products.ProductID = od.ProductID
LIMIT 10Analysis Report Two - Systems Integration and Decision Support
Executive Summary
Businesses rely on information systems to keep daily operations running and help managers make better decisions. Transaction Processing Systems (TPS), Management Information Systems (MIS), and Enterprise Resource Planning (ERP) systems all work together by collecting data, turning it into useful information, and sharing it across the organization. These systems help improve communication, increase efficiency, and support better decision-making.
Research also shows that having more data isn’t always better. Companies need accurate, organized data if they want to use analytics and AI successfully. The best approach is to build strong information systems first and then use new technologies like AI to support business goals.
Introduction
Information systems help businesses collect, organize, and use data to make decisions. Transaction Processing Systems (TPS) handle everyday activities like sales, inventory updates, and customer purchases. They are designed to process large numbers of transactions quickly and accurately.
The data collected by TPS is then used by Management Information Systems (MIS), which organizes it into reports that managers can use to track sales, inventory, and overall performance.
Enterprise Resource Planning (ERP) systems take this one step further by connecting different departments, such as finance, human resources, inventory, and customer service, into one system. Because everyone shares the same data, communication improves and managers can make faster, more informed decisions.
Together, TPS, MIS, and ERP turn everyday business data into useful information that helps organizations operate more efficiently.
Outside Research
Research shows that organizations perform better when their information systems are integrated instead of operating separately. According to Chou, Tripuramallu, and Chou (2005), combining ERP systems with Business Intelligence (BI) helps companies turn everyday transaction data into useful information for managers. This allows managers to identify trends, monitor performance, and make better decisions using real-time data.
Hou and Papamichail (2010) also found that organizations using both ERP and BI systems make better decisions than those relying on ERP alone. Their research shows that organizing data into meaningful reports helps managers respond more quickly to changing business conditions.
However, integration also creates challenges. Pekša and Grabis (2018) explain that ERP systems collect large amounts of data, but companies still need decision-support tools to analyze that information effectively. Without the right tools, employees can become overwhelmed by too much data.
Overall, these studies show that collecting data alone is not enough. Organizations gain the most value when they integrate their systems, maintain accurate data, and use business intelligence tools to turn information into better business decisions.
Data Visualizations
Include the code and graphs for your two visualizations here (One using a two-table join, another a three-table join). You should describe your data and the visualization, together with an explanation of why the example is relevant for modern organizations. Make sure you utilize the new geoms introduced this week
Warning
Remember, the practice covers certain specific concepts. Your grade is based on how well you show mastery of these concepts. Your queries can be loosly based on Practice queries, but they must extend or adapt the practice in interesting ways.
Visualization One - Two Table Join
Important
For your required live edit this week, you must add a table to your two-table join, making it a three-table join LIVE, explaining why you are doing it at each step of the way and demonstrating what insights you can gain from adding another join and using the data it gives you access to in your visualization. Rerun your visualization to show how the new join extends your visualization in some interesting way.
#ggplot visualization in this block. I prettied this up with labels to show what is possible.
ggplot(data = myquery1,
aes(x = Quantity)) +
geom_boxplot() +
theme_minimal() + # Cleans up the background grid lines
labs(title = "Product Quantities")
title = "Distribution of Product Quantities"
subtitle = "Data taken from Northwind"
x = "Quantity ordered"
y = ""
caption = "Source: Northwind Sqlite"Visualization Two - Three Table Join
-- Include another three table join visualization here. This should be completely separate from your two-table join and show different tables, data etc.
--Put your SQL code in this block
SELECT Suppliers.Country, Categories.CategoryName
FROM Suppliers
INNER JOIN Products
ON Suppliers.SupplierID = Products.SupplierID
INNER JOIN Categories
ON Products.CategoryID = Categories.CategoryID
LIMIT 10#Put your ggplot visualization in this block
ggplot(data = myquery2, aes(y = Country, fill = CategoryName)) +
geom_bar() +
theme_minimal() +
labs(title = "Freight Charges by Product", subtitle = "Data taken from Northwind", x = "Number of Products", y = "Supplier Country", fill = "Product Category", caption = "Source: Northwind SQLite")
Recommendations for Industry
Companies should continue investing in systems that connect departments and make information easier to share. ERP systems help improve communication, reduce duplicate work, and give managers a better view of the organization. Businesses should also focus on keeping their data accurate and organized before investing in AI. Good data leads to better reports, better decisions, and more successful technology projects. Finally, organizations should remember that collecting more data is not always the answer. Using the right information at the right time is often more valuable than simply collecting as much data as possible.
References
Getting your citations out of Google Scholar and into your references.bib file takes just a few clicks.
Go to Google Scholar and search for the paper you want to cite (for example: “What’s your data strategy”).
Look directly underneath the search result for the Cite button (it looks like a double quotation mark ”). Click it.
A pop-up window will appear showing standard citation styles (APA, MLA, etc.). At the very bottom of that pop-up, click the link that says BibTeX.
A new page or plain text block will open showing some bibtex code. Paste that block of text into your [references.bib] file.
If you have multiple sources, just keep pasting them one after another down the file. You don’t need commas between the different articles; just separate them with a blank line to keep it clean. You can then cite them like this (DalleMule and Davenport 2017) and they will automatically appear in the references section.
DalleMule, Leandro, and Thomas H Davenport. 2017. “What’s Your Data Strategy.” Harvard Business Review 95 (3): 112–21.