I purchased the Light L16 camera recently and was excited to do some photo tests. I decided to compare it with my iPhone 7+ and Sony RX10 IV. I’ve included a sample image from each device below. However, the iPhone 7+ really doesn’t compare to either of these cameras so I’m not going to include it in the following review.
The Light L16 has great photo quality. In fact, the detail when zooming or cropping is impressive. It certainly beats the iPhone 7+ and Sony RX10 IV. Notice the difference when zooming into the photo and cropping – the Light L16 is definitely superior.
The level of detail from the Light L16 in unmistakeable. In this area the Sony RX10 IV can’t compete. That said, I’m not sure how often I’d need to zoom or crop my photos.
The pixel quality of the Light L16 is also higher and more impressive. It comes in at 10432 x 7824 while the Sony RX10 IV comes in at 5472 x 3648. Wow! Again the Light L16 impresses. Of course, the file size is much different too – 35.1 MB vs. 7.7 MB (a big difference).
Ironically the area in which the Light L16 really suffers is … well … light. Notice below the lack of shadows and light that the L16 simply is not able to capture.
I was incredibly surprised by the difference. The light and shadows greatly affect the picture quality and aesthetic of the overall capture. This was a big disappointment. I really hope that Light is able to improve on this – but to me the limitation is more of a hardware issue and I don’t think it can be properly addressed with software updates.
When comparing the overall image quality the Sony RX10 IV wins. Of course, it’s not as easy to take on the move as the Light L16 but if I were taking portraits or on vacation I’d rather have my Sony RX10 IV. The following are all unedited:
This is an update to a previous post (Uber Passenger Rating) because Uber changed the steps to access your Passenger Rating. Why would you want to see your Passenger Rating? The rating system was created by Uber to help their drivers make decisions about whether or not they want to pick up the passenger requesting a ride. So your rating can have a big impact on how quickly you get service from Uber drivers. In fact, if your rating drops too low, you may struggle to get lifts, or even be booted off the service entirely. Uber does provide suggestions to improve your rating. You can find those here.
Here are the steps to learn your Uber Passenger Rating (you can screen captures below too):
1. Open the Uber app
2. Click the Profile section located in the top-left
3. Select “Help”
4. Tap “Account and Payment”
5. Choose “I’d like to know my rating”
6. Tap on “Submit”
In just a few seconds Uber will display your rating on screen (previously you had to wait for an email…this is so much better!).
While on a trip to Destin, FL USA (first time) my wife and I stayed at an Embassy Suites (Hilton brand) hotel. It was a nice hotel, staff were friendly and it was convenient for our trip. I was excited to see the beautiful Destin beaches, but I have to admit that I was almost more excited to try out a mobile feature at a hotel which I had not yet been able to use – a Digital Key. Yes, the Embassy Suites at Miramar Beach was equipped to offer a digital key via the HHonors app. I took advantage of the app to check-in, choose our room and then accepted the digital key. I was ready!
Digital Key Experience
Overall my experience using the digital key was great. It started with a few pains though…to activate the digital key I had to go to the Front Desk and request help. Ultimately they needed to “verify my credit card” by swiping it. A little odd, but once it was activated (which took a few minutes) it was very useful. While I did also request a physical key I never used it. I was able to unlock outside doors (post 10pm) and my room door with ease.
The advantages of the digital key for hotel guests are a bit obvious, but I’ll detail a few from my perspective:
No need to request new physical cards or have them re-programmed because they’ve stopped working. I recall a recent stay at a Marriott in Virginia Beach, VA USA – I had just finished a workout routine at the gym (on the first floor). I took the elevator to my floor and when I attempted to unlock the door I get the unfortunate red light on the door lock indicating the key card did not work. This was particularly frustrating because I had to go to the Front Desk in the main Lobby after having been in the gym for 45 minutes. Not cool 🙁
Related to the aforementioned benefit I did not go through the typical shaming by hotel employees when requesting a new or re-programmed key card (“did you have it near your wallet or any magnetic devices?”). When you just need a key and not an accusation the digital key option is fantastic.
Super convenient. I always have my phone, I don’t need to get the digital key re-programmed at any moment during the stay, I don’t lose the key, I won’t worry about leaving it behind at check-out, etc.
The only thing which could have made it better was a more seamless integration with my stay. In other words, having to “check-in”, as it were, to activate the digital key defeated part of the convenience. I imagine a stay in which I’m able to check-in on my mobile device, choose my room, and activate my digital key without interacting with a human being. I arrive to the hotel and just walk to my room. That would be nice. For now, I have to congratulate Hilton on what they’ve done, it truly was a good experience and look forward to the next time I’m able to use the Digital Key.
As a Data Scientist I love working with data. I especially enjoy creating stunning visuals to help make data insightful and actionable. As such I’m always interested to see new tools in the market. One area that really intrigues me is BI on mobile. Today, I don’t think there’s one product that addresses all of the needs of mobile BI particularly the social / sharing component. That said, there are some good ones out there. Here are two really good options I’ve been able to use.
I spent some time in Solana Beach with the folks at Roambi and I think they have a stunning app. I had a chance to play with Roambi Analytics and Flow for several weeks and came to really love both. I think Roambi Analytics is probably the best Mobile BI app available when it comes to visualization and interactions. They now have a new app, Blink, that is free and allows you to do basic visualizations by importing CSV files from several cloud storage services (Dropbox, Box, Google Drive, iCloud Drive, etc). This is a part of the latest version of Roambi Analytics. Once you download it, open the app and select “My Projects” to get started.
Vizable by Tableau
Tableau released a mobile app that is also free to use on iOS – Vizable. This is a great mobile BI app. The interactions are natural and easy-to-use. You can pinch to add fields, swipe to filter, drag to reorder, etc. The longest “training” video is only 10 minutes – it’s easy to use. It is also very simple to add data. Especially since it loads data from XLS and XLSX files (by comparison Roambi Blink uses CSV only) because these are more commonly used when sharing raw data within a company; you probably have one in your Inbox that you can add right now.
Unfortunately it does not include any social features and sharing is limited. You can share screen captures via Message, Email, etc but you’re not able to edit or annotate them before sharing. While there’s certainly more to be added I think you’ll enjoy using it. You can download it here.
While Apple introduced a Split View mode in iOS 9 for iPad users to be able to use two apps side-by-side, it did not allow users to open two Safari windows side-by-side. A new app called Sidefari from developer Francisco Cantu allows users to have two webpages open side-by-side. I tested it recently and found it to be very useful and easy to use.
The app works by using Safari View Controller to open a second webpage via Split View. To activate Sidefari, all a user has to do is open the Slide Over app picker and choose Sidefari. The app also works in multiple sizes, allowing users to use Sidefari to take up either half the screen or smaller. Sidefari is only available for the iPad Air 2, iPad mini 4 and iPad Pro as they are the only devices that support multitasking.
When building dashboards and business intelligence applications you’ve likely spent many hours identifying key metrics. You may have even developed use cases and profiles so that your application or dashboard is a success. These steps are an excellent investment to ensure the final product will be engaging and satisfy the needs of your stakeholders. A very important step is defining what visualizations or charts you will use. There are many different chart types you can use, each with it’s own unique way of displaying data, and even slight variances of the same chart type (e.g. Bar Histogram vs. Line Histogram). So take the time to choose the right charts.
To Be Considered…
Use charts that are user-friendly and easy to understand. Common graphs such as line, bar and area charts can achieve this. Avoid any chart that requires a viewer to dedicate extra time to understand the data or its relevance. One of my least favorites charts is the circular area or spider chart. I have found that few users understand it. And if a user doesn’t understand it, no matter how beautiful you think it is, it’s actually useless.
Eliminate unnecessary ribbons, shading, outlines, and icons. This is what many term “chart junk.” It does not provide clarity or insight – it only serves to distract from the main purpose of the visualization. So avoid it. Please.
You can, however, use color to add meaning. For example, you might use similar coloring for objects that are related. I might add a blue hue to charts for air, orange for car, and green for hotel. This helps group like charts visually and has minimal impact on the design.
If someone that was not involved in the design and development process can immediately understand your application or dashboard you’ve done it right. If not, it needs to be adjusted.
What do you want to see?
Most charts can be grouped into four categories: 1) Comparison, 2) Distribution, 3) Composition, and 4) Relationship.
These are used to compare values to each other and can be used easily to identify the lowest and highest values in the data. They can also be used to compare current vs old thereby visualizing an increasing or decreasing trend. For example, you might visualize airline utilization or air volume of current year compared to the previous year. Charts in this group include Bar, Line, Circular (Spider), and Tables.
Distribution charts allow you to visualize how quantitative values are distributed along an axis from lowest to highest. Looking at the shape (or size) of the data a viewer can identify elements like range of values, central tendency, shape and outliers. Charts from this group can be used to to see things like average ticket price by time of day (e.g. Early Morning, Morning, Afternoon, Evening, Late Night). Or they could be used to view # of Trips by Total Spend by Department. Charts in this group include Histogram (Bar and Line) and Scatter plots.
Composition charts are used to see how a part compares to the whole. Or alternatively how a total value can be divided into shares. A composition charts shows the relative value but some charts can also be used to show the absolute difference. The difference is between looking at percentage of total and value of total. These can be used to see market share for a vendor(s) or distribution of booking behavior (e.g. Agent vs Online). Charts in this group include Pie, Waterfall (which I love), Stacked (Bar or Area), and Tree Maps (I like these too!).
Relationship charts are used to see the relationship between the data and can be used to find correlations, outliers and clusters of data. These are actually some of my favorites charts when used appropriately. I used a Scatter plot in one project to see the impact on clients for late deliveries. In a separate project I used one to find which client requests should be prioritized (that required a weighting logic to be applied to the data too). Going back to the travel industry, I used a Scatter plot in a dashboard application to visualize the average ticket price by airline (with the Y axis as number of trips). Charts in this group are primarily Scatter plots with perhaps some variances such as bubble size.
Choosing the right charts might seem trivial but it should not be underestimated. The wrong charts can cause confusion or distract from the story your dashboard is designed to communicate. Take the time to make sure you’ve selected the visualizations that will best contribute to your application becoming a success whether it’s use is external or internal.
I recently published Beautiful Data Visualization – Part 1 in which I discussed some of the challenges with data when it comes to creating compelling visualizations. I also offered some suggestions of tools and processes to build confidence in your data sets. Now that you’ve taken the first step to great data visualization (or at least formulated a plan to do so) it’s time to start developing those visuals which will provide executives, managers, directors, and the like with the insights needed to make smart business decisions.
The Starting Line
To begin you must have an objective. In many cases these directly answer very specific questions. “How much does it cost us when deliveries are late?” “What is our spend compared to budget for the current year?” Now you can begin to review the available data which will be used for analysis. You’ll be able to identify any gaps that an auxiliary data set can fill and become familiar with data you will be working with while developing. Finally, the more exciting part! Prototyping. You get to brainstorm and design concepts for visually the data. Some questions you’ll want to answer are: What data will you use? What type of chart or visualization is best for your objective? Are additional indicators or comparisons required? Once you’ve set the requirements or parameters you are ready to create a mockup for approval.
As you build your visualization give consideration to making it as natural as possible to be actionable. Many business intelligence tools and visualizations do not provide actionable information. This is what I call linear business intelligence. What we want to create is a natural method of discovery that leads to action. While some of that does rest on the data underneath your visualizations, the latter cannot be underestimated or taken for granted.
This is why it’s very important to consider what type of visualization is best. There are some 21 different chart types that I would consider using. But they each have their intended purpose. Some are for comparisons, others for composition, some for distribution, and a few for relationship (we’ll discuss this in a future post). This is why we start with knowing the objective, asking questions, reviewing the data, and then creating mockups. This is what will lead to the use of the most compelling visualization.
Here is a real life example of a travel dashboard I was tasked to create. I knew that I needed to create a consolidated view of travel spend. I knew that I would need to bring together multiple sources of data. And I knew that I needed it to be actionable. So I started it with three important metrics: 1) Spend vs. Budget, 2) Online booking performance (goal vs. actual), 3) Traveler gamification based on booking habits. The other metrics complement those and lead to further analysis as necessary. The final product was impressive and eventually lead to an entirely new product offering.
Know your primary objective.
Ask questions to have a complete understanding of the project and what it will be used to accomplish.
Review available data that will be used for analysis and to power your visualizations.
Prototype. Create mockups and get approval from stakeholders before development.
Post development provide a sneak peak internally or with the project owners and get feedback.
It’s hard to find beautiful and compelling data visualizations. Even when using tools that provide the ability to create stunning visuals many product offerings fail. It’s certainly true that “big data” and proper analytics can deliver actionable insights leading to smarter decisions. Yet, the value of said insights depends greatly on the quality of the data. Larger data volumes and it’s variety make it more difficult to establish confidence. What’s to blame? Does it really matter?
The Blame Game
It’s not uncommon for analysts and other stakeholders to blame the tool. When executives are not able to make confident decisions with the data, reports, analysis provided the tool is often ‘thrown under the bus’. But is that really the issue? Analysts are expected to use available data and tools to provide insights. It hardly seems appropriate then to blame the tool for decision making shortcomings. Rather, the analyst provides additional information and expert advice when the tool (or the data) creates gaps in business intelligence.
This brings us to the data. We’ve all heard something similar to ‘garbage in, garbage out’ in reference to bad data. While that statement is, at it’s basic definition true, it does not need to be true in practice. There are many tools available for auditing and cleaning data. Examples in the data industry are R and DataWrangler (which eventually was spun off into Trifacta). Google has a tool called Google Refine. There are several products in the travel industry too such as Cornerstone’s DataCleanser application or Grasp Prepare from Grasp Technologies. I suppose the point is that you should be using a data auditing product.
Common Travel Data Audits
Ensure data is in correct currency
Identify and delete duplicate flights caused by split ticketing
Identify missing hotel names, chains, and rates
Delete duplicate hotel and car information caused by improper invoicing
Is it worth it?
If you like to make good decisions then it is well worth the effort. In a survey recently released by IBM it was reported that companies with <70% data accuracy were unhappy with their decisions 2/3 of the time, companies with >90% data accuracy gave executives reliable information 4 out of 5 times, and companies with high data quality saw >24% improved performance last fiscal year.
Beautiful Data Visualization
You’ve now taken the first step to great data visualizations. It’s time to start developing those visuals which will provide executives, managers, directors, and the like with the insights needed to make smart business decisions. How will you do it? Where do you start? We’ll discuss that in Beautiful Data Visualization – Part 2!
Most travelers aren’t aware that after using Uber drivers are rating those whom they pick up. What’s also a little known fact is that you can have Uber send your average rating. The rating system, which uses a one through five scale (five being the best), was put in place by the company so drivers can learn more about what to expect when they pick up certain passengers, and, in theory, decide whether or not they want to pick them up in the first place.
The ability to request your rating is hidden deep in the Uber app settings. I decided to request mine and in less than a minute I received an email informing me “Your rating is an average of all your trips taken so far. At this time, it is 4.7.” I suppose that’s not bad out of 5. But it’s nice to know that Uber helps you get a better score. Check it out here. You might also like to know that according to Uber “Ratings are always reported as averages, and neither riders nor drivers will see the individual rating left for a particular trip.”
Interested to learn your rating. Here are the steps:
The use of a radial interface was pioneered in 2012 and is making a comeback in the past year especially with wearable tech. One advantage of using circles in a touch interface is the ability to have more points adjacent to your finger at the same distance when touching the screen. With squares, the path to the next item would be variable and there would be a smaller limit to the number of items you could fit around a touch point. On smaller displays, circles can be scaled easily to reflect popularity or usage and can be organically tessellated to fit more items on the screen. It seems this circular UI pattern will pop up more in the future for small displays and touch interfaces, giving interaction designers more flexibility to reflect natural movement in their digital experiences.
It seems that this also lends to the extremely desired and useful ‘one-hand operation’. Apple, for example, uses this radial interface in their Apple Watch products but they also included one hand operation in the iPhone 6 interface. The new Reachability feature provides access to all of the top-of-the-screen elements that might otherwise require a second hand, and iOS8’s new thumb-friendly recording interface for Messages shows that same Path-like consideration for our favorite digits and their natural range of motion. Clearly, Apple has decided that making devices accessible with one hand is crucial to winning the wearable market.
Modern business models show that making things quicker often yields positive results. Apple has introduced a suite of new features intended to make our life easier, including a more robust system of Contextual Responses within the new Apple Watch OS, which will provide “quick” responses for iMessages based on the context of the ongoing conversation. This is a brilliant idea. But can it go beyond simple text processing to providing information to the user based on what we think they might like. I would really love to see how this can disrupt travel – especially when combined with GPS and iBeacon technology.
Imagine: It’s Tuesday morning, and you just woke up. Based on your calendar, Apple knows you have a meeting at 9 a.m. but most days you get to work at 10 a.m. Usually you get a coffee on your way to work at Starbucks around the corner, and Apple knows this by passively monitoring your GPS positions over time. So how can Apple make your life easier? What if your Apple Watch could take this data and calculate the best time to leave based on your average walking speed, anticipating a coffee stop and how long it usually takes you to get to your office?
Or if you’re going to visit a client in Windsor and you’re traveling from London. You have a train ticket purchased on South West Trains from London Waterloo to Windsor and Eton Central station. Based on the client contact information in Contacts (or perhaps with integration into Salesforce) Apple knows that you’ll have a 53 minute train ride, and a 10 minute walk to the client office. It also knows that you’ll pass the Starbucks at 18 Thames Street. It suggests an upgrade on the train so you can work with Wi-Fi, walking directions that will have you pass the coffee shop and even prompt you when you arrive to Windsor and Eton Central station if you’d like to pre-order your favorite beverage.
This concept isn’t new. Predictive Analytics has been under development, somewhat publicly, for the past few years, and has been implemented with mixed success in everything from the Google Now app to Netflix’s recommendation engine.
Implementing predictive analytics in your own designs can be as simple as considering how to refer users to the next step in a process, or as complex as detailed behavioral analysis algorithms. Tools such as KISSmetrics and Google Universal Analytics can be employed as a basic data store to monitor usage. As the field grows, interaction designers should keep an eye out for new off-the-shelf platforms for implementing detailed predictive analytics in their own applications.