



I got a hold of a free trial software of SAS Visual Analytics. So far it is a pretty fun business intelligence reporting tool. Over all it is easy to use as well. Below are a few graphs that you can make out of SAS Visual Analytics.
Created a chart that shows the Product Cost of Sale by Facility Continent

Created a box plot that shows the Product Cost of Sale by Product Line.

Created an automatic chart that shows the Unit Capacity by Transaction Date where the date format is in “Year, Quarter”.

Created a tree map visualization that shows Product Sale by Facility Country.

Created a 3 different graphs using product sale for each country in South America.



Created 2 different graphs of product sale of “Kiosk” product line in Vancouver and in Toronto from 2010 till 2012.


Create a graph showing the two months of 2012 the cost of sale was lowest in Atlanta.

Creating visualization 1 we decided to use categories of Facility Continent, Facility Country, and Product Line. The measures Product Sale, Product Cost of Sale, Product Price (Target), and Product Material Cost.

This bar chart graph allows us to check each Continent of the Product Sale and Product Cost. As you can easily see that there is a high volume of sales in North America.

This graph allows us to dig into North America in United States and lets us drill down deeper into sales into each State. Also we have split brand by Novelty and Toy. As we can see Toy has a high sale volume than Novelty in the overall sale from each State.

This line chart allows us to see quarterly sales in North America, United States region. There is a trend line can be easily determine by showing 4th quarter increases in product sale while 1st quarter seems to be down time on product sales.

This descriptive chart of product sale and product Cost by North America, United States region in a table format that list detail of each product sale and product cost. Easily allow users to see line items of product sale and product cost for product line.

This bar chart allows us to compare material cost, product cost, product sale, and potential price target for North America, United States region. Also to expand on the product sale to certain product line to see what the volume for each category. Figurine and Game seem to have the high volume of sales.

All in all SAS Visual Analytics let’s marketing target peak quarters and allows finance to plan forecasting for next year. Also allowing cost and sales to be broken down from Continent to Regions to even States, it really lets us drill down into the detail of data.
This is my chart using an old data from PDA users. Decided to run a position graph on what consumers rate PDAs. As you can see Compaq has the highest average from attributes while Connector has the lowest. My goal is to help market Connector PDA.

Using the data I have made a position map of what consumers think of each product. I’ve broken these into 3 clusters. Connector PDA has the lowest mean but has greatest connectivity. It would be best to try to market Connector PDA with it’s best attribute which is connectivity.

Pros about positioning you find benefits of the products and the weakness of the products. Disadvantage of this graph is that it may be misleading and its a snap shot of the current data you have on hand.
Executive Summary
The goal of this proposal is to fulfill and provide all the needs and requirements, various applications, and data rate to support Mr. Johnson’s landscaping business needs. Mr. Johnson’s landscaping business needs are 5 desktop PCs that run on Windows Operating System with Microsoft Office. These PCs will all be connected to the laser printer and AT&T U-Verse modem. Also the PCs will also have various applications needed to help with other business needs of Mr. Johnson’s business.
With all of Mr. Johnson’s landscaping business needs kept into consideration I have put together a business plan. The business plan has all the software and hardware needed to run Mr. Johnson’s landscaping business. A logical network diagram will be shown to see how Mr. Johnson’s business network will work. The technology design is all the specific detail of each recommended hardware and software that will fulfill your business needs done under research of your business needs. Also taken into consideration of future growth of your business.
The last section of the report will have a cost assessment of all the recommended hardware and software cost. It will also have the variable cost and labor cost that is all invested into Mr. Johnson’s landscaping business.
After doing extensive research of your business needs I believe I have the solution of fulfilling all of Mr. Johnson’s business needs.
Network Analysis
Needs Analysis
Needs and Requirements
Various Applications Necessary to Support Those Needs
Data Rate Needed to Support Those Applications
Using the Web to access scheduling would use 0.5mb.
Logical Network Diagram
A logical network diagram of the network based on the network requirements and the functionality of the Physical topology of the office set up of the network creating a Local Area Network (LAN).

Technology Design
Hardware and Software Specifics
Netgear DSL Modem Model 7550
Cisco Small Business RV110W-A-NA-K9 Wireless-N VPN Firewall 5000 Simultaneous Sessions 90 Mbps
CISCO SYSTEMS SG100D-08-NA 8 Port Gigabit Switch
HP Pavilion 23-g040xt All-in-One Desktop PC
HP LaserJet Pro 400 color Printer M451nw
Now that every hardware specific is described from above in detail. The technology design Mr. Johnson’s business will consist of AT&T U-verse internet of 54Mbps. The AT&T U-verse intent will be connected Netgear DSL modem Model 7550 sold by AT&T. The Netgear DSL modem Model 7550 will be connected to the Cisco RV110W-A-NA-K9 Small Business RV110W Wireless N VPN Firewall Router. The Cisco RV110W-A-NA-K9 Small Business RV110W Wireless N VPN Firewall Router will be connected to CISCO SYSTEMS SG100D-08-NA 8 Port Gigabit Switch.
The cables of Coboc CY-CAT6-25-WH 25ft. 24AWG Snagless Cat 6 White Color 550MHz UTP Ethernet Stranded Copper Patch cord /Molded Network lan Cable will be connected to the five HP Pavilion 23-g040xt All-in-One Desktop PC. All the 5 HP Pavilion 23-g040xt All-in-One Desktop PC will be connected to the HP LaserJet Pro 400 color Printer M451nw.
As you can see this would be the structure of Mr. Johnson’s business. All the hardware design and how all the hardware architecture structure of Mr. Johnson’s business with detail hardware specs for each component.
Cost Assessment
Fixed Cost
Tax and shipping cost are not included in these tables.
| Brand | Description | Cost | Quantity | Total |
| HP | HP Pavilion 23 g040xt | 799.99 | 5 | 3999.95 |
| HP | LaserJet 400 M451nw | 399 | 1 | 399 |
| Netgear | Model 7550 Modem | 100 | 1 | 100 |
| Cisco | Business 100 Series SG100D-08 Switch | 54.99 | 1 | 54.99 |
| Cisco | RV100W-A-NA-K9 Router | 69.99 | 1 | 69.99 |
| Coboc | Cat6 25-WH | 4.42 | 1 | 53.04 |
| Total | 4676.97 |
Variable Cost
The variable cost of quantity are calculated on a per month basis. This cost will extend over the period of 36 months or unless a cancellation is made for some reason.
| Brand | Description | Cost | Quantity | Total |
| AT&T | U-verse 45 Mbps | 64.95 | 36 | 2338.20 |
| Email provider 5 users | 25 | 36 | 900 | |
| Total | 3238.20 |
Labor Cost
Labor cost is an estimate and can subject to change depending on the situation.
| Labor | Description | Rate Cost | Hours | Total | ||
| Network | Network Set up | 250 | 8 | 2000 | ||
| Computer | PC Set up | 250 | 3 | 750 | ||
| Maintenance | Upkeep 2014 | 250 | 3 | 750 | ||
| Maintenance | Upkeep 2015 | 250 | 3 | 750 | ||
| Maintenance | Upkeep 2016 | 250 | 3 | 750 | ||
| Total | 5000 | |||||
These are all the cost that will fulfill Mr. Johnson’s business needs and requirements as of 7/13/16. A lot of time and preparation of choosing the best and affordable product for Mr. Johnson’s business needs. With all the business needs, technology design, and logical network set up can be executed.
Background
Most projects proceed in the following manner. Every month, the State publishes “the book,” which highlights the projects to be let that month. The company requests plans for jobs for which they may bid. Jack, Bob and Frank review the plans and at least one of them makes a site visit. The bids are then completed and submitted to the state. During the bid writing process, suppliers for various line items (concrete, steel, paving material, paint, etc.) are contacted for their prices. Since the suppliers are qualified by the state as well, this is a simple matter of calling up and asking for the unit price for the material. In fact, since the suppliers are privy to the same information as the contractors (as well as who has requested plans), they will often call up Wilco, with the total cost (unit cost and amount already calculated) for a line item on a particular job.
If Wilco is “low-bid” on a project, they assign a supervisor, who is responsible for the site administration. The supervisor (Jack, Bob, or Frank) takes a crew to a job site, and accomplishes the various tasks needed to complete the job over the few months that the project will run. The job site supervisor is the final authority on the administration of his particular job. The client will also assign an inspector (usually an administrator and/or an engineer) to the job site as well. Equipment and trucks are owned by the company, which can be moved to the various job sites by tractor and trailer. In some cases the job site supervisor needs a piece of equipment that is too specialized for the company to need on every job, hence equipment is sometimes rented.
Wilco Construction is an open shop, that is, employees may or may not belong to a craft or trade union. Jack and Bob believe that the decision to join a union should be up to the employee. The bulk of Wilco’s employees are not union, however, simply because there usually is not enough specialized work within one trade to keep any worker busy all of the time. The State mandates that all workers be paid a union scale per hour rate based on the skill classification for the job that they are doing at any given time. Consequently, there is no financial advantage to joining a union. The varying pay scales make for a complex payroll calculation. For instance, if a worker spends 2 hours as general labor ($11 per hour), 3 hours as a carpenter ($12 per hour), 1 hour in masonry work ($13 per hour), and 2 hours as a heavy equipment operator ($15 per hour) in a given day at a given job site, then their wage would be calculated by taking the amount they earned in each classification and summing those totals. In this instance the worker would gross $101 dollars for that day. Additionally, the wage scales can change from job to job (based on distance from the nearest union hall). For example, on a job 10 miles from a union hall, the union scale for an iron worker would be $14 per hour, while for a job 50 miles away from a union hall, the scale for an iron worker would be $15 per hour. The scale for each job is supplied by the state with the construction plans. Employees working on non-state projects (or at the shop) receive $10 per hour, regardless of job classification.
Wilco’s workers are extremely flexible, and move from skill to skill and job site to job site on a daily, even hourly basis. The only constant at a given job is the job site supervisor. For example, last week when Frank’s crew was getting ready for a big bridge deck pour, Jack spared a few of his workers to help out, as his project was temporarily delayed (heavy rain had flooded a footer hole, which had to be pumped out before work could proceed). Consequently, a worker may have worked at multiple sites, in up to 5 skill classifications (general labor, carpentry, masonry, ironwork, and equipment operation), in any given week. All of this has to be taken into account to generate a payroll statement. The job site supervisor is responsible for keeping track of most of the movement of employees from job to job and site to site, however, trusted employees who have been with Wilco for several years keep their own time cards. At any rate, all information relevant to payroll eventually gets turned into Mary.
Recently, employment equity legislation has also become an issue in the construction industry. Currently, legislation dictates that employers use certain percentages of visible minorities and women for each job skill classification on each job. A report stating how many hours (on each job, in each skill classification) were worked by women and visible minorities has to be sent to the Ohio Equal Employment Opportunity Commission (EEOC) every two weeks to demonstrate compliance. Currently, 10 per cent of all hours in each skill classification at each job (although the wages are not consistent across jobs, the skill classifications are) have to be worked by a woman or visible minority to be in compliance with the regulation. Failure to comply could mean that Wilco would be stripped of its qualification, making it ineligible to bid on state contracts. In addition, as governments change, the legislation changes, and hence the reporting requirements change as well.
Project
As a group we gathered the project requirements:
First we need to make a Data Flow Diagram to help give us an understanding of how data is used for Wilco Construction. I used Microsoft Visio to create this diagram.

The next process we needed to make a database using Microsoft Access and created a Entity Relationship Diagram. As you can see the many connections through the 15 tables we have created.

After that we created a form for the “Employee Entry Form”

By this time we were already almost finished with our project. We created a Work Flow Diagram to show the procedure how the time card would work on this remote check in.

This is our prototype of Wilco time card entry which is also simple and user friendly interface. We used Microsoft Visual programming C# to create this time entry system.

If for some reason a worker has forgotten his card he can ask the manager to help sign them in. It will also let the users switch to different jobs that they are capable of doing for a different wage.


Software
Software used are Microsoft Excel, Tableau, and Notepad.
Source
Found my salary of MLB players through http://www.baseballplayersalaries.com/ and performance statistics through http://mlb.mlb.com/stats/ for 2014 season.
Data Extraction
Extracting the data with a simple copy and paste to a notepad.
Process
This process was easy since the data was easy to find on MLB’s website. It was an easy task of copy and paste to a Notepad and then uploaded to Microsoft Excel. This point I just had to clean the data which was simple. The next step was adding their salaries to Microsoft Excel which was a simple task of looking players up from http://www.baseballplayersalaries.com/ . After the data has been cleaned it was then uploading it to Tableau. Tableau allows you to drag and drop attributes you want use. I use scatter plot graph for my visual on this project. It allows you to also see clusters of players’ performance relative attributes I wanted to see.
Analyzing the Data
The visualization of my first graph using Tableau’s scatter plot has 1B representing position first base players. The x-axis has HR as home run and the y-axis Avg as avg hit per ball. The plots are circled with different sizes which determine their salary. The bigger the plots the bigger the salary of the player. Also the plots are different color to represent different players.The great part of using Tableau’s scatter plot is that it allows you to visualize the performance of a player by certain attributes and see if they are performing anywhere near what they are getting paid for. Also it can help show clusters of where most players stats are around.
As you can see for the first graph there is about 4-5 different clusters depending how you cluster the players together. The graph also lets you see outliers (a plot that is completely no where near the others) for example Jose Abreu of 36 home runs and a batting average of 0.317. Also you can see some players salaries aren’t as big, but still perform as well as high paid salary players for example Anthony Rizzo.
The same explanation is for the other graphs with different position of players of 2B (second base), 3B(third base) and so on.
The great thing about Tableau under each graph you make they explain the attributes you use and the detail of everything that needs to be explained about the graph produced from Tableau.
Software
Software used is Microsoft Excel.
Source
Finding Major League Baseball salary through http://www.usatoday.com/sports/mlb/salaries/2014/team/all/ .
Data Extraction
Extracting the data with a simple copy and paste to a notepad.
Process
The process of this was a simple copy and paste to a notepad. After that I upload the file to an Excel and cleaned the data and sorting the data to my preference. The next step was sorting the data by “Salary” largest to smallest for each year. After that filling the team with proper visual analytics colors.
Analyzing the Data
The visualization shows MLB team salaries from each year from 2004 to 2014. Each column represents the lowest (bottom) to the highest (top) paid salaries. All the World Series Championships winners (highlighted orange) are aligned horizontally to easily compare relative team salaries.
I’ve also wanted to show a simple bar chart from 2004-2006 graph made with excel to compare the different visualization techniques.
Both charts have its’ pros and cons. If I wanted something to pop out with a quick glance the first graph would be better, but if I wanted detail data the second graph would be a better choice.
The question we have to ask “Does a higher salary equate to a better chance or more World Series Championships? “
Software
Software used are NODEXL an open source for social media analytics and Microsoft Excel.
Source
Twitter has become a big source of big data text analytics and a big social media platform.
Data Extraction
The process of extracting tweets from http://www.ifttt.com using my own formula of if new tweet then create a new document.
Process
The process of this you must have an twitter account to link up with http://www.ifttt.com account that lets you create your own recipes of “if -> then” statements. I created a statement of gathering twitter tweets with hashtags of #kershaw (LA Dodgers pitcher). He currently won the CY award and I knew I would be able to gather a good amount of social media data. My “ifttt” account collects #kershaw tweets from users and updates the tweet to my google drive account. After gathering all the data and converting the file to an excel file to upload to NODEXL.
Analyzing the Data
Each node is a completely different color and shape indicating a twitter user. The tweets with circle are just normal tweets not mentioning anyone or replying towards anyone. For this case people are just tweeting #kershaw on their twitter account. The tweets with a line and arrow are tweeting towards someone else, which in this case is tweeting towards “ClaytonKersh22” with twitter hashtag of #kershaw. As you can see the area of the map with a lot of concentrated arrows pointing towards ClaytonKersh22’s account.
It just shows how easy it is to gather data from a social media source and use the data gathered and create some sort of explanation of social media data.