Studio711.com – Ben Martens

You may remember a previous post about a product called SpinRite. It’s a hard drive maintenance and recovery tool, and it’s handy to have it in my bag of tricks. It has always been slightly annoying to use though because it requires me to dedicate a machine to it while it’s running and it can easily take a day (or even a week) to run.

Last week I had cause to run it again and after futzing around for a long time trying to get it to run on a spare laptop (it wouldn’t see the USB drive that was connected to the laptop), I started to wonder if I could get it to run in a virtual machine on my main desktop. SpinRite uses very low level commands to access the drive and I didn’t think that would work inside a VM, but why not try anyway?

Sure enough, it did work! Here are the steps I did:

• Attach the USB hard drive dock to my desktop and insert the drive.
• Power up the drive and wait for Disk Manager to recognize it.
• Set the disk to Offline mode.
• Create a new VM in Hyper-V (I’m running Windows 8.)
• Use SpinRite.exe to create an ISO and set the VM to boot that ISO.

From that point, SpinRite could see the drive, and I didn’t care how long it took to run because it wasn’t blocking me from doing other work on the machine. Perfect! Theoretically I could even spin up multiple instances of the VM and point it to multiple drives to parallelize a big recovery job.

I’ve written a couple times before about my Power BI project at work. The head of our group gave a presentation at the Worldwide Partner Conference that provides a nice overview of our future roadmap. To view it, go the WPC keynote page, click on “The Cloud for Modern Business” and then skip ahead to the 21 minute mark when James Phillips comes on stage.

Last November, I posted that I was switching my email from GMail to Outlook.com. It didn’t affect anyone because it just meant that my @studio711.com email forwarded to a different site, but it was a pretty major change for me.

I did it in large part because I want to dogfood the solutions that our company provides in hopes of fairly representing them and offering feedback to the teams that wrote them. I thought it would be a bit of a downgrade, but wow, I’m really impressed. Outlook.com is a fantastic mail service. First of all, their junk mail detection is just as good as GMail. Where they really shine is their interface. Outlook.com loads faster and is subjectively easier to use, especially if you’re on a touch-enabled device. The web client looks and acts very similarly to the Windows 8 app so the continuity is a plus. I manage all my email in the desktop version of Outlook, but their web client and Windows 8 apps are so good, I’m thinking dropping the client version of Outlook.

This wasn’t the side-step (or even downgrade) that I expected. It’s pure win. If you’re frustrated with your email service or just looking for a change, give it a shot.

Yesterday I wrote about the process of losing weight, but I only alluded to data sets. Let’s dig in! My data sources were the Fitbit API (for both number of steps and weight) and some weather history which I’ll explain later. This all came into through Power Query.

First of all, here is a chart showing my weight over time and then which days of the week. I usually gained weight on Sundays (our days to get together with family), Tuesdays (taco day in the café at work) and Fridays (the day we sometimes go out to eat.)

Next up are some charts showing the number of steps I took each day. The chart on the left shows how often I took a certain number of steps. The chart on the right shows the total number of steps each month. Note that we’re only halfway through June so that bar is shorter.

I fully expected to see a correlation between the number of steps I took on a given day and the amount of weight that I lost. Nope. Here’s a scatter plot showing no correlation. I think that walking is good for weight loss if you’re very overweight and you don’t move much. But there’s a point where walking is just too efficient to do much additional good.

I then started looking for other possible data correlation. Maybe the number of steps that I took was related to the temperature? Nope.

We’re in a wet part of the country so maybe the amount of rain we get in a day dictates how many steps I take? Not really. My really big days have happened when it doesn’t rain, but just because it’s dry doesn’t mean I’ll walk a lot.

In the end, I took all the various data points and ran them through Excels correlation algorithm. Nothing came out showing any real correlation. The biggest one was one of the charts you see above: the bigger the high temperature, the more steps I take, and even that was only a 0.48 correlation. That’s skewed quite a bit too because I’ve been doing a LOT more yard work lately and it has been warmer.

Even though I didn’t find a scientific way to lose weight, I did learn lots of things that AREN’T related and that’s interesting too!

The general media has picked up on a huge bug that rocked the tech world this week. I’m sure it’s partially because it has such a great name and logo. But what is Heartbleed and how does it affect you?

This isn’t a virus or malware that affects your computer. It’s a bug in some very critical code that is run by a lot of web servers. Basically, it gives out somewhat random chunks of computer memory to anyone who asks for it. That memory usually contains gibberish but sometimes it will contain things like user passwords or keys to the encryption of all the traffic going in and out of the server. The webcomic xkcd has a very simple explanation of the bug.

There are a bunch of things that need to happen to fix the hole. First the server admins need to patch their systems, get new encryption keys, and replace their SSL certificate. Once that happens, you can complete the final piece of the puzzle by changing your password. Some websites are being proactive and telling you when they’re ready for you to change your passwords. Others are being more quiet about it.

This whole thing has been *gasp* overhyped by the media. Yes, it’s a potentially big vulnerability but the odds of someone exploiting you are low, the patch is relatively quick and easy, and there’s evidence that nobody launched a widespread attack using this vulnerability before it was announced. That being said, updating your passwords is still a good idea. There are various lists around the internet that tell you which sites were affected, but this is one a pretty good resource. They are updating it regularly and telling you when it’s time to change your password (if you need to change your password at all.)

If you’re changing all these passwords but you aren’t using a password manager, consider getting started with something like LastPass.com. It’s free and easy. If you’re already a LastPass member, run their security checker tool. They’ll tell you which of your passwords need to be changed. LastPass was affected by Heartbleed too, but because they encrypt all of their traffic even underneath the SSL encryption, there’s no chance that any of the LastPass data was exploited.

So don’t fret about this too much, but do make sure you’re changing passwords as needed.

I know I’ve been making a lot of Power Query posts lately, but once you get into it, you start seeing data everywhere! The latest example is a movie draft that I participate in with some friends. I won’t explain what a movie draft is except to say that it’s like fantasy football for movies. We participate in a huge league run by Brian Brushwood and friends. They post a spreadsheet with all the data here: http://draft.diamondclub.tv/

I pulled those spreadsheets into Power Query, cleaned up the data, and voila, now we have an easy way to track just the people in our little group! You can see it at http://bit.ly/excelmovies We get interesting views like a leaderboard just for our group, and a list of the movies left for each one of us. I might add some more data views later, but these are the basics.

So if you’re in our movie group, how can you use it? You can use it passively by just visiting that bitly link every once in a while. I’ll update the data periodically for your enjoyment.

If you want to update the data yourself, add your own friends to the list of names to watch, and/or learn how the workbook was built, then you’ll need to do a little extra work.

1. Install Office 2010 or 2013
2. Install Power Query. If it fails then you don’t have the the right version of Excel. Sorry, you’ll have to stop here. (I continue to tell management that I think this is a bad decision.)
3. Go to the bitly link and click Edit Workbook > Edit in Excel
4. Save the file as a local copy.
5. Click Data > Refresh All and wait a bit. When the status bar along the bottom of Excel completes then you should be seeing new data.
6. You can see the Power Query queries that make up the workbook by clicking the Power Query ribbon and then clicking Workbook. You’ll see a side pane appear and you can double click any of those queries to start digging in.

Unfortunately I think Step 2 is going to stop a lot of you, but at least you can view the online link. And if Power Query doesn’t work with your version of Office, please feel free to complain in our forums!

If you’re running Windows 8, you probably got a pretty big update this week. The Windows team has been listening to the feedback and has made some pretty key tweaks to improve your user experience. PCWorld says “This digital love letter should woo over all but the most obstinate of the PC faithful.” So what’s included?

The user experience is tailored depending on the type of device you’re using. If it’s a traditional mouse and keyboard desktop computer, you’ll boot to the desktop and media files get opened in the desktop version of the apps instead of the full screen Modern App experience. Additionally, you can right click on tiles on the start screen and there’s a bar at the top of the screen for full screen apps with common controls like minimize, close, etc. Those full screen Modern Apps will now show up in your taskbar on the desktop just like any other app.

There are a couple other tweaks, but those are probably the biggest things you’ll notice after you apply the update. Go forth and enjoy! And keep giving feedback not just on Windows but on all your favorite Microsoft products. They listen!

A while back I wrote a post talking about the cameras we’ve set up around the house and the software that manages it all (BlueIris.) There’s nothing terribly new in this post except to give a long term test update and say that I’m LOVING this setup. The garage cam lets me easily check to make sure that I remembered to put the garage door home or see if my family is home so I can ask Tyla to defrost some meat for dinner. And since we don’t regularly use our front door, the camera there is a great way to know that we have a package waiting or that someone left a flyer in our door. I even get an email showing a couple images and a 5-second video of whoever was at our door. All of the cameras are great but those are the two that I use the most regularly and I’m eager to add some more coverage.

If you ever want help with a similar setup for your house, let me know. I’m happy to share info. You can get going with one camera and the software for around $100-$125 and then each additional camera after that is about $65. You technically can skip the software but it makes life a lot easier.

In yesterday’s post about all my Amazon orders, JonathanC posted an interesting comment: “How about this one as a Power BI challenge: current value of the portfolio if you had purchased stock of Amazon instead of the product.” … Challenge accepted!

I already had a list of all my Amazon orders. I think headed to Yahoo Finance and downloaded a daily history of Amazon stock stretching back to 2001 when I made my first product purchase. That came as a CSV file too. Both files got loaded into Power Query. I did a merge on the date column, removed the columns that I didn’t need, and added a custom column that was the money spent divided by the closing share price that day. That told me how many shares I could have purchased. A quick sum over that column divided by a sum of the money spent revealed that I would have made an 81% return on my money! But wait a minute, transactions aren’t free. If I was pay $8 per transaction then I would have only made a 37% return. But that’s silly since I probably wouldn’t have bought $10 of stock at a time like I do with Amazon orders.