Deep Dive – Data Vs Information


01100111 01110000 01110011 01110010 01110101 01101101 01101111 01110010 01110011 00101110 01100011 01101111 01101101

You probably don’t know what the above says, other than a bunch of binary numbers. The numbers are below:

103 112 115 114 117 109 111 114 115 46 99 111 109

These are, in fact, ASCII codes. They say “”. Refinement of raw data is what makes it useful. I think we can all agree that a binary interface is almost useless to humans, although some older computers did display the binary using lights. What I’m seeing though is that very few people realise the same is true of fitness data. Raw data is useless unless you’re very experienced, and even then it’s time consuming and error prone to use in that form.

Pyramid showing data, information, knowledge and wisdom. Data is at the bottom, wisdom is at the top

This diagram is the information pyramid. It shows how the processing of data makes it more useful. Raw data at the bottom is just that: data. A bunch of datum’s (the single form of data) gathered together. In running this would be a location, current pace, or cycling maybe current power in the right pedal. Not useful. Gather these and process them though and you can create information. That information might be heart rate zone during a workout phase at a given pace. Much more useful, hence the term “information” is used rather than “data”. This information is valuable to humans. We can go a step further, though, and create knowledge. This would be using lots of information to create something actionable. For instance how is my heart rate at a given pace over time. This gives me the knowledge of whether I’m improving or getting worse. If we have enough of this knowledge we may even be able to create wisdom. At these heady heights it may be the case that we can learn how to make something happen.

In data analytics, we often show the below diagram. This is kind of what we’re going for any time data is involved. As you move along to the right things get harder, but value goes up exponentially.

Image shows the four levels of analytics from descriptive to prescriptive and how value increases along with difficulty of processingOn your watch, you’ll see the “what happened”. As you run it tells you how fast you’re going, where you are, climb rate etc. Really fancy watches may also give you some more insight, such as telling you your steady state workout produced a certain outcome for fitness. The wider app and platform is (in theory) there to dig into things further and take you up a notch.

I say “in theory” because as we all know they don’t really, do they? Garmin have more fitness data than just about anybody on the planet. You’d think they could get a handle on what works and what doesn’t, and be able to properly feed back to us. They won’t. Not yet. Until they absolutely nail this technology they have a problem. Their business is driven in part by coaches and trainers. And these people need you to need them in order to survive. And you’ll likely buy whatever they use, because they use it. The far right of that graph up there is where machine learning and AI start to appear. We’re already there today from a technology standpoint (trust me, it’s not even that hard!). What we need to do is spend time and energy training the bots, and testing them.

What’s that, you say? No way to replace a human? If a human can make a decision in less than a few seconds, a machine can make the same decision faster. Coaches have a set of rules in their heads which they made through training and experience. Machine learning not only does this too, it does it faster and more accurately with less superstition and bias, AND it can use billions of data sets rather than the few hundred a human could handle.

Anyway, that’s the future. That’s when we won’t need the information display because we’ll be told what to do. Not been for a run in a month? Your watch will beep loudly and suggest you get off your fat ass. Probably Fenix 6 or 7 will do this. For right now, you need to interpret your data or get a coach to do that for you. And this is where we turn the data into information.


Graphs are easy, right? Just a few numbers, a couple of axis.

Here is the Garmin heart rate graph. I didn’t have a heart attack, don’t worry, I just own a Fenix 5. Imagine the gaps aren’t there. This is data. The only way this would be worse would be to have the raw numbers printed in a table. What am I supposed to glean from this image exactly?Garmin also allow you to switch to a different tab and see how long you spent in each zone. Again, I’m not sure how this really helps aside from knowing it was mostly a zone 3 run.

Again with the pace graph, I can barely read this and it certainly doesn’t allow me to see my pace easily for the different intervals. I can hover over with the mouse, but then why bother with a graph? Next we have the Suunto graph (different run). It’s spikier. That’s literall all the value I get from this compared to the Garmin. It also looks cooler, like someone with a design degree was involved at some stage. Garmin is all engineer all the time. No designers in Kansas.
Suunto also include a bar chart for zone time. You don’t have to switch tabs, just scroll down so there’s a little more value seeing them side by side. Lots of wasted space, but it does have a certain charm.
And finally Polar. It’s important to know that Polar are very sports science focused and they also happen to make some devices to enable that. I feel as though Polar may have some designers, but they weren’t allowed much input here. The engineer was told exactly what to produce. The real input, I assume, came from someone who does sports things for a living. This is not data folks, this is information. At a glance I can see which zone I was in, and how well I was keeping within that zone. I could see if I was at the top of the zone the whole time, or near the bottom, and I can see instantly how long in each next to the graph. Someone thought this through.

Mixed Graphs

Sometimes it’s handy to see HR or some other metric against pace. Garmin allows you to expand the graph to do overlays.

Polar don’t do overlays, but I think I forgive them because the below is very useful indeed. You’d almost be able to tune your speed zones to match HR zones, which would be cool!

And the Suunto support it too.


Tables can be made more interesting too. Tabular data isn’t the most exciting, but sometimes it is useful. Here is the tabular data on Garmin of my recent swim. Here we can easily see the set totals but also expand to see the set data. We can also very easily see rest intervals, something quite important for swimmers. Swim repeats are one of the most used methods in swimming, and Garmin helpfully supports the “repeat on” function to allow you to start your next lap at a given time. For instance, repeat 100m on 1:45 would mean that if you swim your 100m in 1:30 you get 15 seconds to rest. As the set goes on your rests get shorter as your times get slower. Seeing this against HR information would be critical to determining efficiency of your technique in the pool (way more important than fitness or strength in swimming).
Garmin also give a nice graphical display of simplified stats. I like this view a lot for quickly seeing what I did on a whole swim before drilling down with the data.

Polar shows a very similar display to the Garmin table. They don’t have graphical mode, but they do have two “killer features” and one drastic disadvantage. Firstly my optical HR works in the pool, so I have that info. It seems accurate too. Secondly, I don’t have to push anything in the pool. Polar detects my stroke, my lengths, my laps, and my rests. My rest timer was identical to the garmin on the other wrist where I pushed the lap button. I was very impressed. It lacks a repeat timer though, so for swimmers it’s not quite there yet. Right now I can rest for 20 seconds but I can’t repeat on 1:45. There’s a very big difference, and you only need to watch swimmers staring at the wall clock to realise they use the repeat timer exclusively.

Polar do, however, show the cool stuff above the graph including HR and automatic laps. This is very nice and lets me see my recovery HR too.

I don’t know how best to say this. I’ve not used Suunto in the pool. Shame on me. I’ll try to fill that gap soon.


Polar are doing great things here. They consistently make information out of data to help me on my way. After I cover on-watch information display I’ll come back and cover the knowledge level aspects of each platform. Again, Polar are out front on the knowledge front (albeit with some bugs…). I’m finding the Vantage V system great for telling me what’s going on between workouts (albeit with some bugs…). On the watch face I can actually have a symbol to say whether to work out or not in a simple easy to use way. That’s a win, and that’s the future or wearable tech. Garmin tells me some stuff too, and one day I’ll investigate how to interpret that jibber jabber. Until that day it’s like I’m a cat reading Shakespear, and that’s a fail. That’s the past.

It’s only fair to point out that although Polar do well in this post I am having several major issues with the Vantage V right now so can’t recommend it as your only device. It recorded a 5km treadmill run as 2km today, and since I got it, it’s told me not to train or I’ll get injured. I did get injured, but that was due to running in the dark in an unlit lane and twisting my foot into a pot hole. Add that to the “oops” I got recently when it crashed and I have to say wait for the next firmware before buying, or make sure you have two devices.

I’ll be adding a second post soon to show you the data/information discussion on the watch itself. Suunto really shine there, and Polar are going places too. Garmin let the engineer have too much say again, and rely WAY too much on people filling their gaps with ConnectIQ. There are still gaps.

Thanks for reading, add your thoughts and comments below, I’m sure you’ll have plenty as usual and remind me of things I should have covered which I’ll add as requested.


  1. This is a terrific post and one of the reasons I’m interested in moving from Garmin to Polar. But although the Vantage looks and feels great, it’s such a dud to run with. The screen layouts feel like they chose form over function and are really difficult to read, even in sunlight.

    Even wearing it as a daily driver to tell the time and activity level can be frustrating.

    I’m tempted to keep the one I have and continue to use it in conjunction with my Garmin so I can build a decent data history, or bail and just find a smarter system to use with my Garmin. The jury is still out.

    • I agree the Vantage isn’t easy to read, but it does present information better than a Garmin so you don’t need to see the numbers necessarily. It is very dark though and the backlight doesn’t always come on.

      I’ve left them out here but Training Peaks and Strava both have reasonable platforms. I’ve heard Golden Cheetah is good too. Realistically though, Garmin can afford to do better at data presentation. They just need to get someone from outside of engineering on the team. Right now a lot of Garmin stuff seems to be done for the convenience of the coders rather than for making a great device. That was necessary to move to the agile platform they have, but now they are on top they will need to go back and address the finesse and design issues. That said, I’m not even sure Garmin think there is a problem. For all I know they might have chosen this design on purpose as cultures differ the world over. If this looks great to American eyes though Garmin need to internationalise quickly before Suunto and Polar take the EU market.

      • >> I agree the Vantage isn’t easy to read, but it does present information better than a Garmin so you don’t need to see the numbers necessarily. <<

        What do you mean by this? I'm generally training with 4 data fields – HR, pace, lap pace and distance. I switch distance to lap distance for intervals. Would you suggest I use a different display configuration for the Vantage?

        I've scrolled through some of the standard screens and they still seem difficult to read while running, but I may be missing a setting or something.

        • I meant the graphical displays are very good. It’s easy to see zone and power info without looking at the numbers.

  2. Is it difficult to read the screen because the text is too small, or because the screen is too dull? I guess it is OK in the dark with the backlight on?

    Can you not configure screens with one, large field to make it easier to read quickly at a glance?

    Even on the Garmin 935, I prefer to limit myself to two fields at most on a screen I want to be able to read while running hard.


    • Mostly it’s just quite dark. The font is fine and when the light is on it’s fine but the light doesn’t come on every time (easily sorted in firmware). Yes you can configure screens easily in the app, and Polar have some very nice graphical options which mean you don’t always need text.

  3. In my opinion there are a few more things to consider.
    First, there are lots of platforms/apps that help you transform your data into wisdom. The original platform is never going to give you everything you need/want. The crucial part for me is the ability to export all relevant data to external apps, the easier the better.
    Second, the ability to import/fix your data. Example: V800 has this recovery info. But one hard session without hrm or recorded by other device (battery went flat, recording failed) will break the recovery chart for a month or two. So I switched to Stravistix and Runalyze for recovery info and ignore V800 completely. No way to import such a session back into Flow.
    Third is accuracy. If your goal is to improve by 5%, don’t get a device that has a 5% accuracy.
    I mean if you have incomplete or inconsistent data you can’t quite expect much wisdom out of it.

    • All good points. I’m working on a post about integration for after these visualisation posts. Similarly the inability to get weight data into Polar is disappointing.

      • I’m not sure what you mean with the inability to get weight data into Polar. In the web version of Flow you go to the day view of the diary and in there you can manually set your day’s weight and save it. I did that for quite a few months and it worked just fine. At some point I bought the Polar scale (because my old one died) and now it works like magic, but in reality it works just as well. The only real difference is the option to set a weight goal, which is surprisingly motivating but not important if one’s focus is on the sports aspect of flow..

        • btw. the one major thing I really miss on Polar is the a1bility to add shoes to runs and track their mileage!
          oh and btw2: Thanks a lot for your reviews and comparisons! I think that choosing the right platform is just as important as choosing the right device! However, for some reason that aspect get completely neglected in pretty much everything that’s out there.

          • Thanks for the comment 🙂 I tend to use Strava to track my kit because I have lots of devices and they do it really, really well. I can even track chain wear on my bikes which is awesome (and led me to ditch ceramic lube, which is EVIL after a chain lasted just 200 miles!). Strava even gives you a reminder after the mileage you set is reached, which is awesome for runners who like new shoes often before the old ones look worn to the eye.

        • What I mean by that is exactly what you say. With Polar there are exactly two choices; laborious manual entry or Polar Balance scales. This, in 2018, is not good. Polar Balance scales are (and indeed were at launch) inferior to almost every connected scale on the market. Since long before Polar even launched their scales I had a set of Withings wifi scales. I don’t need to take a device to the bathroom with me, they just upload to the Internet. They also download previous weight data along with weather data to show me first thing in the morning, because they have direct web access.
          But the important part, and the part that Polar do not understand, is that they also connect via API to almost every other platform out there. While Garmin integration is a bit shonky (via a third party) it just works. I have NEVER told Garmin Connect my current weight, but all my Garmin devices have it nonetheless. As does Strava, and many others. Integration is key to success these days and until Polar understand who owns the data they will always be a small also-ran in the industry. Garmin, for all their faults are pretty open albeit often on their own terms. They created the fit file format but opened it up. Ant is an open standard, and Garmin were one of the first to allow transfer of data from their platform. They also added BTLE sensor support despite the fact that their own Ant+ is better for sports use. Every time Garmin have been open their market and share in those markets have grown. They aren’t the biggest because they have the best stuff, they are where they are because they enable people.
          As I’ve said to Polar, I have no intention of ever buying Balance scales. Not only does that mean I don’t give them a sale, it also means that the Vantage V functionality is severely hampered too. Who’s the winner here? I’ll use my Garmin or Suunto while they get poor reviews and negativity online. Not just from me, most fitness bloggers pick them up on this.

    • I pretty much agree with the post.

      One of the interesting things with Garmin is that the basic analysis of a metric (eg pace) over time is rubbish, yet Garmin Connect DOES have higher level insights from further up the insight/wisdom pyramid. Strange.

      import/fix – yep i agree with your points. And you have to have the ability to manually add a value of ‘X’ to whatever is missing eg in sporttracks I can add an estimate TRIMP value if the HR breaks/spikes or if forget my watch.

      accuracy is important for some things and less so for others. eg did i achieve the target pace in my 1 minute intervals requires accuracy of both the actual WORK time period and the speed. whereas TRIMP needs, at a guess, 95% HR accuracy for meaningful calculations and insights that follow.

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