Week 11: Clear

Image created by Josh: http://www.flickr.com/photos/geojanitor/2432843590/

Data vs. Information. Is there even a difference? Most people, when they hear these two words, equate them to each other. I, for the most part, was one of those people. It's so easy to give in the dark side and say, "Hey, data is the same thing as information." This isn't true. But, the truth is easy enough to understand. Data is raw facts and figures: how many home runs Roger Maris hit in 1961 (a record setting 61 for you non baseball fans) or the number of licks it took to get to the center of a certain Tootsie Pop (the world may never know). Information, on the other hand, is data in context. It is used to answer questions and to support decision making. Information is a trend line where data is the scatter plot. Data is the ammunition. Information is the gun.


I am a HUGE fan of the relationship between data and information. It sounds sad now that I say it, but it is true. I'm currently in a Statistics for Business Decisions class and I love it. AP Stats was one of my favorite classes in high school. Stats is all about taking vast tracts of data and turning it into information. The fact that I can take thousands of numbers and turn them into a single solution to a problem fascinates me. The more data I have, the more confident I can be with my conclusions. The more data I have, the closer I can be to the truth. Probabilities and confidence intervals all come from data. When something so simple can be so powerful, you have my full attention.

Data is extremely important in the business environment. As I mentioned above, statistics is all about making decisions based on data. A class I am taking right now is specifically about statistics in a business environment to make business decisions. Without data, managers would not have information. Without information, managers are not informed. Without being informed, managers can not make good business decision. It all starts with data.

Database Project

I got the opportunity to work with FileMaker Pro 11 this week. You may remember the Excel Project I completed a couple weeks ago. This was very similar in regards to organizing data and making it more useful. I already had a good deal of experience with Excel, but with FileMaker Pro 11 is was starting from scratch. I had never used this software before. Consequently, I learned a great deal more than I did with the excel project. 

• The first skill I learned was how to set up validation of fields. This is very useful in reducing the number of careless errors that appear in a given report. You can either make a list of acceptable "values" that can appear in a certain field, or you specify acceptable values using an equation with operators. Validation is helpful, but only scratches the surface of what FileMaker Pro is capable of. 
• Next, I learned how to create forms using the layout function. This is more of an organization and aesthetic tool. Forms show a single entry with all specified fields. You could make a form that only lists name, birthday, and gender. I don't know how that particular information would be useful in a business environment, but it could be done. Forms are a very clean way of displaying data. 
• The penultimate skill I learned was how to use queries, or "finds" in the case of FileMaker Pro. It's a simple procedure of filtering data by whatever you want really. You want to see all the people with birthdays after January 18, 1975? Easy. How about all the people who are male, from Orlando, and have two dogs? As long as you have a field for gender, city, and number of dogs, you can find this information with a few clicks. 
• Best of all, I learned how to create reports. Yay... Reports, while boring, are a powerful tool for sorting data, organizing it in a clear format, and getting it ready to print. With reports, there are no limitations to how you can sort your data. You can apply finds and print out targeted data. While I learned a lot about FileMaker Pro, there is still so much to be learned. 

There are only a couple enhancements that I can think of that would improve the effectiveness of the database. The first would be a validation for both the Join Date and Left Date. These should be validated through an equation that would not allow dates before the company opened or after the current date. It would be a simple validation and would help to avoid simple errors while entering dates.  It might also be useful to add a saved find that shows all people who have left the gym. By using the find "<=//" in the left date field, only people who have left the gym will show up. These are a couple changes that could reduce mistakes and make the database more useful. 

I also attempted to create a script. I feel that it went very smoothly. I didn't run into any problems, and it worked exactly as I thought it would. There are certain situations in which scripts could be incredibly useful, but for this project it didn't improve efficiency at all. It was a good learning experience for when I use scripts in the future. 

Week 10: Clear

This week I've been working on something special. If spreadsheets get you excited, hold on to your magic carpet, because this week was all about database software! I know this is the moment you've all been waiting for... Now, even though I know none of you were anticipating this particular blog post, database software is a pretty powerful tool in the business environment. This week, I was able to work and learn with FileMaker Pro.

This software is much more powerful than a traditional spreadsheet. One of the capabilities I really loved was the ability to sort through massive amounts of data so easily. Whether it be quantitative or qualitative data, you can find what you need FAST.

Going into this week, I had no experience with database software whatsoever. It was completely new to me. Excel was the paragon of data organization. FileMaker Pro really opens the door to a whole new world (Cue Disney music) of capabilities. Seriously, cue the music...

A couple of the things FileMaker Pro can do that leave Excel behind are:

• Safer Databases and Tables- Now when I say safer, I mean that there are less possibilities for mistakes. There is a fancy trick called "Validations" where only certain values are allowed in certain columns. This greatly cuts down the number of mistakes. In a way, it is a built in proof read.
• Queries or Finds- This makes it much easier to sort through massive amounts of data. You have a class of 500 students and you want to see how many of them are Freshman? Simple. You want to see of those Freshman, how many received an A for their course grade? No problem. Finding information has never been easier. 
• Forms- A wonderful way to sift through more detailed information of a specific field. You can easily see all the grades a certain student received on every assignment throughout the semester. Cluttered data suddenly becomes clear. 
• Reports- Simple procedure to get summary statistics of large groups of data. You can get the summary statistics of a certain field, the whole set of data, or even both on the same sheet of paper. 

Database software goes above and beyond spreadsheet software in so many ways. In baseball terms, spreadsheets are the minor leagues and database software is the "the show". If you want to be apart of the major leagues of business, you should really know your way around database software. It improves efficiency and clarity in ways I could only imagine before this week. 

Week 9: Muddy

Moore's Law in itself is easy enough to understand. It states that the number of transistors that can be placed on an integrated circuit doubles every eighteen months. This is heavily intertwined with computer performance as well. Computers have been, essentially, doubling in power every eighteen months for decades. But we have come to a point where Moore's Law is in danger of slowing down significantly.

"The important thing is that Moore's Law is exponential, and no exponential is forever... but we can delay forever."      

-Gordon Moore 

Moore himself stated that Moore's law will not last forever. There is a cap on all things, including technology. But have we reached that cap yet? Some scientists believe that we are very close to reaching that cap while others believe we still have a few more decades left under the expansion outlined in Moore's law.

Where things got confusing, to me, was when I started researching what kinds of technology are being researched to keep computing power on the rise. There were a bunch of different ideas I ran across including: silicon nanowires, extreme ultraviolet lithography (EUV), molecular computing, DNA computing, and quantum computing. From what I understand, the idea is to make everything smaller and more efficient without overheating. A few of these ideas are outlined below.

• Silicon Nanowires- Utilizes a highly efficient cylindrical transistor. This geometry provides the highest efficiency because the entire surface area of the wire is conducting. More in depth (and technical) information can be found here: http://www.theregister.co.uk/2012/03/16/silicon_nanowires/
• Extreme Ultraviolet Lithography- Etches computer chips with a wavelength of around 14nm while currently technology uses a wavelength of 193nm. This will much more efficient but is not currently precise or controlled enough to be put into effect. More on EUV and other potential lithography techniques can be found here: http://www.theregister.co.uk/2012/03/15/euv_challenges/
• Quantum Computing- While this is probably the farthest possibility on the horizon, there is the most potential in it. Scientists were able to perform basic multiplication problems using only 5 atoms. Think about that for a second... Scientists were able to prove "3x5=15" with only 5 atoms. That is incredible, but the technology is still very, very young. 

This is another video I found by Michio Kaku talking about several possibilities in the future of computing and some of the problems scientists face trying to bring the technology to the public. Video can also be found at: http://bigthink.com/ideas/42825

 

For a final note on Moore's Law, here are Adam Savage and Jamie Hyneman.

Excel Project

For this project, I was tasked with formatting, manipulating, and analyzing data in a variety of ways using Microsoft Excel. Personally, I was using Microsoft Excel 2004 on a Mac. While this did not affect my ability to fully analyze and format the actual data, it did affect the formatting of the pivot tables. We will get to that a little later on. 

The most important part of this project, in my opinion, was to manipulate the data using accurate formulas and functions. Without accurate formulas and functions, the analysis is wrong. When the analysis is wrong, you are wasting both the time and money of your employers. There were five new columns that I was tasked with creating. The columns, along with the formulas used and procedure of manipulation, are listed below:

1. Maximum Heart Rate (MaxHR) - This was a very simple formula. The calculation was simply to take the subject's age and subtract it from 220. I inserted the formula "=220-B3" for the calculation for subject 1 and copied that formula all the way down the column. Because I used relative cell addressing, the age (B3) changed according to row/subject ID.
2. Target Heart Rate (TgtHR) - For target heart rate, I used the formula "=D3*$E$1". D3 is the maximum heart rate column and cell E1 is the percentage of MaxHR that was desired. In this case, it was 80%. The absolute cell addressing was used for E1 because it allows a single cell to be changed to a new percentage instead of having to alter the formula each time a new percentage is desired. 
3. Highest Heart Rate Achieved (HighestHR) - I used the MAX function, "=MAX()" in order to determine the max heart rate achieved by each person during the workout. Ex: Formula for subject 1 was "=MAX(I3:AC3). I was able to copy and paste this formula down the column because it used relative cell addressing. 
4. Target Achieved (TgtAchieved) - This required the IF function. By using the formula "=IF(F3>=E3, "Yes", "No") for subject one, the cell would read out "Yes" if HighestHR was greater than or equal to TgtHR or "No" if HighestHR was less than TgtHR. This was copied down the column with the use of relative cell addressing. 
5. Heart Rate Increase (PctIncreaseHR) - The formula for this calculation was "=(HighestHR-StartHR)/StartHR". For subject one specifically, this formula was "=(F3-I3)/I3". The cell was then formatted to read this decimal as percentage. 

While these formulas were the most important part of the project, the formatting helped to make it look presentable. Simple formatting like centering, bolding, italicizing, and restricting decimal places was used. Column widths were also adjusted. Formatting the page for printing was also a simple matter of going into "page setup" and altering a few things. In order to keep the first two rows at the top of the page at all times, I used the Freeze Panes function under the Window drop down menu. 

AvgIncrease Pivot Table

Last, but certainly not least, I created the pivot tables. This was the most difficult part for me because I was using Excel 2004 while the lectures used a more recent version of Excel. But, I was able to find the Pivot Tables function and use it without too much problem in order to find the number of people, both male and female, who reached their target heart rate and the average percent increase for various age groups and gender. The pivot tables are not as pretty in Excel 2004, but I tried to format them to make them as attractive and clear as possible. 

I learned a couple new excel tricks while completing this project. My favorite new "trick" was the freeze panes ability. That is very useful when dealing with large quantities of data. I also learned all about pivot tables, which are essential in analyzing large quantities of data. Luckily, I was already familiar with all the functions and formulas needed to manipulate the data. This sped up the process immensely. While I knew a fair deal about excel already, I feel I was able to round out my abilities and increase my efficiency when working with excel.