With Azure Machine Learning being released to General Availability this week (Feb 18th, 2015), more interesting news come to life.
There is a couple of (somewhat confusing) options to try and use AzureML. Better to be informed before you jump in and register your account with Azure…
AzureML Free Tier
With GA, Microsoft decided to release a free tier to make easy for you to try the service. The difference with the classic Azure trial is that you don’t need an Azure account for this (which requires a valid credit card).
Another difference is what you can do with this type of account: you’re not on trial time (one month, one year), but bound by other type of limitations such as: data storage (10GB), number of modules per experiment (100), max experiment duration (1 hour) and performance (throttled).
Still this is the best option if the only thing you want to do is to give AzureML a try, or even use it as a development environment before you move into production.
This is the classic Azure trial: you will be given 1 month and $200 that you can use to try any Azure service, including AzureML. It will require for you to register a new Azure account, and enter your credit card information.
AzureML Pay-per-use
After your one month trial expires, you can check the current prices here.
Different options for different goals
If you just want play and try some small experiments: Use the Free Tier. Most small experiments will be run just fine.
If you are ready to take your experiments to the next level, and release to production: Start with the Azure one month trial. After one month, you will be billed at the regular rates.
I’ve just got a new Dell XPS 13 2015, and all I can say it good things about it. I’ve been a faithful Mac convert since 2004, but after 10 years, I feel its the right time to come back to the PC and Windows.
Even through all these years, I always kept working on Windows, MacOS seemed a more stable and uniform environment, but with Windows 8.1 and the coming Windows 10, I think Microsoft is really coming back. Besides, the quality of Ultrabooks in general now matches (if not surpasses) the ones from Apple.
I bought a Yoga 3 Pro earlier this year and ended up returning it after less than a week, because of its lousy performance. Don’t get me wrong, I loved the chassis and design in general, also the 2-in-1 factor seemed cool at the beginning. But honestly, couldn’t justify the machine being slow after just opening two or three tabs on IE, unacceptable.
Now, straight to the Dell XPS 13: this is the Ultrabook to have in 2015. I’ve been following the XPS 13 for a couple of weeks now, and it was nowhere to be found: neither Dell, Microsoft, BestBuy or any other online retailer had it in stock.
Screen: Touch screen or matte?
The first option you have to deal with is the screen: if you want a touch screen is around $100 more, but also the resolution is awesome: 3200×1800 (even higher than a MacBook Pro Retina Display). The only drawback is the glossiness… I love matte screens, I’m sure I will find a matte screen protector for this.
The brightness at its maximum is really good, also has an auto-brightness setting that works pretty well and saves you battery.
Final comment: Just go for the non-touch if you must, the real deal is the 3200×1800 QHD touch screen. The resolution is excellent.
i3, i5 or i7?
The processor is the second big decision to make: i3 is not an option for me (having discarded the Yoga 3 Pro for having a Core M, which is even better than the i3). The only real options are i5 vs i7. This was a tough call, as I found the i5 reduced $100, so the gap between these two was $300. Too much of a price difference just for a couple more GHz and cache. Honestly, don’t think the i7 is worth it, unless you plan to keep your computer for a long time.
SSD Space: 128GB, 256GB or 512GB
128GB is out of the question: you either get 256 or 512. If I would have found the 512 n stock I’d buy it, but 256GB was the only thing I could get. Besides, the good news is that (apparently) you can upgrade the storage. If not, you can add more storage via an SD card.
Where to buy? At the Microsoft Store of course!
There are lots of retailers that can sell you this, but your best bet is still the Microsoft Store. Their service is superb, comparable experience to what you get at an Apple Store. When I was at the store an still undecided between the i5 and i7, they didn’t try to upsell me straight to the i7, but walked me through the considerations they would have, and ended up recommending the i5. That’s really honest!
Other advantages are:
– Signature Edition PCs: Your Windows is pre-installed by Microsoft and with no manufacturer adware, malware or bloatware. This is excellent, now that we’ve heard what just happened to Lenovo and its infamous Superfish.
– Microsoft Complete for PCs: Kind of an extended-warranty, but at $129 it definitely makes sense! Apple charges around $300 for the same on their Macs. Whatever problem you have, you can go to the Microsoft store and they’ll fix it for you. It covers up to two damage incidents during the two year warranty, and they will give you a new PC for just $49. Really hope I don’t have to use it, but you never know..
Overall comments
I’m very happy with the Dell XPS 13, the non-bezel display is gorgeous, the keyboard is very comfortable and the performance of the i5 model is excellent. The portability is very similar to a MacBook Air 11 (and that is not a typo).
Overall, a very minimalistic machine with excellent performance and at a reasonable price.
Azure Machine Learning (aka AzureML) is one of the new products/services in this new bold world of ‘cloud first, mobile first’ that Microsoft is endeavouring. It helps you create predictive analytics from your data in a very quick and simple way, and easily integrate this with allyour applications. And you can do that armed just with your browser!
But I think I’ve heard about this before… Haven’t I?
Remember a couple of years ago everything was 2.0? Web 2.0 was the paradigm everyone swore by, adding ‘social’ and ‘services’ around all we already knew by then.
That is how I feel about Azure Machine Learning: it is a great, improved 2.0 version of the old Data Mining concept we’ve known for years (SQL Server implemented this with its SSAS Data Mining feature). Don’t take me wrong, I’m not saying that because this already existed one will quickly discard it. I think Microsoft took a page of its own book, and put a lot of thinking on how to bring that into 2015. And that is great!
Out with the old…
If you remember, Analysis Services Data Mining always had a couple of algorithms you can use:
Classification algorithms predict one or more discrete variables, based on the other attributes in the dataset.
Regression algorithms predict one or more continuous variables, such as profit or loss, based on other attributes in the dataset.
Segmentation algorithms divide data into groups, or clusters, of items that have similar properties.
Association algorithms find correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis.
Sequence analysis algorithms summarize frequent sequences or episodes in data, such as a Web path flow.
To use them you would create a model in SSAS, load data (with help provided by SSIS) to train the model, and then you can use them through DMX (Data Mining eXtension) queries. Doing DMX queries involved connecting to SSAS using native windows-only proprietary drivers and then sending these queries to get back your results.
… and in with the new!
The principle behind AzureML is pretty much the same. Couple of notorious diferences here:
– You don’t need SSAS: In fact, you don’t even need SQL Server at all: no database, no SSIS, no SSAS. This is a pure online service, born into and for the cloud. There’s been talks about bringing it to on-premise, but honestly I don’t think that is going to happen any time soon (and nobody would blink an eye either).
– Data loading and manipulation inside the tool: As mentioned before, you don’t need SSIS. Your expermient designer in AzureML has a workflow view that resembles SSIS in the sense that you have components to scrub and manipulate data before loading into your model. One less thing to worry about.
– No DMX or weird query languages to use: As this is a cloud service, the output of your model is a web service. Anybody (with the correspondingAPI key) can call it and make use of your model. This makes your model available and online-ready in really no time.
– Integration with R: R is ‘THE’ language to create models. In the old world, you could still create your own models using the SSAS Data Mining SDK (using C++ or C#) but they would still have to be compiled into native windows code, deployed, managed and available only through SSAS. Being able to take any R algorithm available and use as a component makes this very much open for experimentation.
– One click deployment to Azure: To deploy your old data mining model used to require creating some kind of component (or service) to wrap the SSAS DMX call. Deploying to the cloud is literally done in one click, and you are ready to go. There’s even boilerplate code provided for you to call the production-ready web service from C#, Python and R.
– Really low entrance barrier: No infrastructure setup, no licensing costs, no development tools setup. The only thing you need to do is register to the AzureML service online and pay for the processing cost when you run your model. That’s it!
Summary
AzureML is one of those products (services?) that makes me excited about the future of Business Intelligence. So easy to setup, work with and deploy that is kind of a crime not using it!
Now, this is still a 1.0 version of a product. Features that are still not there or missing:
– Heavy data encryption: Training models often involve highly sensitive / private data. Everybody requires a trusted and heavily encrypted transport for this data. This is where most of the asks are going to come from: people coming from the Enterprise world concerned about their data travelling through public networks.
– Easy model retrain: Model re training is something it should be done frequently. Once you train your model, you need to keep it up to date to respond to environment changes and also potential decreasing accuracy. There is no easy way to automate this right now.
– More algorithms: This is mitigated by the fact that you can infinitely expand by using R, but still this is where most of the grow will come from. Also, Microsoft recently bought Revolution Analytics, so I would expect more algorithms and features added.
Your next steps
If you’re interested in using AzureML, just register a new account (there’s a 1 month, $200 trial) and just start using it. Some resources you can use to start learning it are:
mongoDB is a relatively new database management system, one of the prime examples of the No-SQL database movement (if such a thing exists). In No-SQL databases, that can also be referred to as ‘non-relational databases’, you don’t represent data tables that store rows and their relations. Each No-SQL database has its own particular way of modelling, storing and representing data.
This NoSQL movement is basically promoting the shift of development and logic on database querying and processing out of the database systems (and SQL language) and into the developer and programming world. I think programmers never liked the SQL language, or never had the time or patience to understand its declarative nature (a declarative language is one where you express a computational logic and not so much a program flow). There were many attempts to lower the impedance mismatch between those world over the years: object-oriented databases, ORMs (object-relational mappers) and even LINQ in the .NET world and their equivalents in some other languages and platforms like Java. I think NoSQL is just another attempt on that, but more specific: their objective is targeted specifically to manage huge amounts of data (popularly known as “Big Data“). Summarizing, where in a relational database you would use SQL to pull data out of the database, in the NoSQL world you would use your system’s programming language.
In the case of mongoDB, data is stored in form of “documents” which are basically JSON strings, some sort of object serialization. If you are a JavaScript or web developer, you are in good luck today, because you are very familiar with JSON, and the way it represents information. If not, you will have a slight learning curve, but nothing to steep to be honest.
Another interesting characteristic on mongoDB is schema management: in a relational database, you first model a table, where you specify the types of data you will be able to store (columns) and their data types. In mongoDB there is no such thing, every data item you store is just a serialization and it can be completely different from any other stored in the same collection.
I’ve been working with mongoDB for the last couple of months, in an experimental way, but now I’m starting to work on it for a project full time.
I had the chance to compare it (more philosophically) with other database systems I worked with, and I’ve come to like it to some extent, although still leaves me with some doubts and wishes in several aspects.
The good
Here are some of the things I really like about mongoDB:
– Free and open source: This model works well for small projects, but you will find costs as you grow. You will want a more robust infrastructure, and mongoDB requires more hardware than other database systems in order to be fault tolerant. Also, you will want some kind of support from mongoDB, and you will have to pay for it. Also, open source means you can take a look at the source code, but mongoDB (the company) still owns the product and the project’s destiny. This means you can start small with free, and then keep growing as you need more.
– Scalable almost to infinity: this is not to say that you will need that, but is more scalable than traditional relational database systems. With the SQL Servers and Oracles of the world, if you want to scale, you would buy a bigger server (more RAM, more HDD, more processing power): this is called scaling vertically. You can see there is a limit to how big your server can be, right? With mongoDB, you will get more inexpensive hardware and add them to a cluster that behaves as just one big server to the application layer: this is called scaling horizontally. There is virtually no limit to how many servers you can add to a cluster.
– Simple JSON API: This is what makes it so popular. Everybody and their mothers who know who to program in JS can now use a very simple API to access a database.
– Very good documentation: All the information you can need is available at mongodb.org. If you need some hand holding, they even provide online courses at education.mongodb.com
The bad, and the ugly
Things I really don’t like about it:
– Not so great in the enterprise environment: mongoDB (the company) is clearly putting all their efforts to push this into the Enterprise landscape, with different degrees of success. I’ve seen some really awesome use cases (like implementations of Customer 360 view apps created in incredible record times) but also some very awful implementations.
– JSON: Yeap, I think this is their blessing and curse. The fact that everybody can simply use this makes it very easy for anybody with absolutely no understanding of database modelling or theory, to make things a mess in record time.
– DBA tooling is poor: And this is something that has been improved over time. As mongoDB relies heavily on their community to create management / monitoring / optimization tools, there is not a clear path or toolset that one can use to work or even develop. Sometimes, too many options can be a problem.
All in all, I would still recommend for you to take a look on it, just to get a glimpse on what the non-relational database world looks like. It is always good to broaden ones horizons.
A lot has been said in the last year about Big Data as the “future” of Business Intelligence, but Big Data is a very weird concept to me.
About Big Data
I understand this idea that we’re accumulating more and more data each year, but still Big Data is an elitist concept to me. How many companies in the world have real big data problems? I’m sure large corporations face this type of challenges more often lately, but I think the real revolution in Business Intelligence is hidden somewhere else…
The future of reporting
People are overwhelmed by the amounts of information they receive, and sometimes can be challenging to understand it. This is one of the most creative solutions I have seen in a long time. AT&T created a video bill for cellphone accounts, so when you get your e-bill you also get a link to a personalized video that explains all the items in your bill so you can follow it through at your own pace.
https://www.youtube.com/watch?v=3Mbkyo_Hz0k
This is not only a very innovative way of presenting information but a clever strategy to lower calls to the company by people trying to get explanations about all the items in their bills. I am not counting on it to replace regular reports, but is a great complement to e-billing strategies.
The future of search
We need tools that help people retrieve all the information they have. Big or small data, there is no storage or analysis challenge that can’t be solved today… by engineers! We need to put the data in the hands of other people: marketing, sales, designers, artists. We engineers already know how to through in a couple of SQL queries and get whatever we need, but is the people (who will NEVER learn SQL or use a simplified query tool) that need to start finding real uses for all the data that we already have.
I tried yesterday the Windows 8 Consumer Preview yesterday and I really liked it. They finally did what I’ve been asking for years: a clean start out of more than 15 years of UI history. Windows deserves another opportunity, and this may be it. One of the ideas I also wanted to see implemented in Windows is this concept of a dual interface: the old traditional Windows plus a simpler interface (kind of a “Windows for Dummies”), because that was what helped the iPad succeed.
I’m still curious about how this “Windows on ARM” project is going to work. I can see many people buying new Windows on ARM tablets (because someone on Best Buy told them they run Windows) get really disappointed to learn that only a small subset of Windows software will run there. This is the moment for .NET and Java to shine, but let’s be honest: how many people know if their software is written in any of these two platforms?
Also I’ve been using Windows Phone 7 for the past week and I have to say I really like it too. I have been faithful to my iPhone 3GS for almost two years until it became so slow that decided to switch and give WP7 a chance, maybe until the iPhone 5. There are only few things that I don’t like about the interface:
– I think the alphabetical list of apps can be improved. Even with the index shortcut, I feel there has to be a better way to arrange apps. I tend to remember more the icon of an app instead of its name, so for me is easier to just look at pictures instead of scrolling through names.
– We need more apps! I’m ultra-happy to have Skype on WP7, which was one of the main reasons why I abandoned it one year ago. Now that’s not an excuse anymore. This is still a beta, but is totally usable.
All and all, WP7 is really fast and elegant, and you can see the platform is becoming a serious alternative in mobile.
I’ve also been using XBox as a Home Theatre Centre for over a year now and I have to admit is the best thing in the market right now. Compared to this, Apple TV is no competition. Being able to have Netflix plus Hulu on the same device is just great!
All of this thanks to the new User Interface design called Metro.
I’m glad that Microsoft seems to be finding its way back.
The Jawbone UP is one of those products I waited for, and really really wanted to have. I’m kind of a gizmo’s junkie; so every new, shiny, data-collecting device released must be in near proximity of my working area field.
What’s UP?
The Jawbone UP is what they call a ‘fitness band’. It is a wristband (similar to the ‘Livestrong band’ but thicker) that will help you measure three things:
Steps taken during the day. Pretty much like a pedometer.
Distance ran while jogging. Similar to the Nike+ stuff.
Hours slept and quality of sleep. What you will get with Zeo.
Nothing new, uh? But what got me is the idea of having three things in just one simple object that you get to carry around all the time, so is difficult to forget. It is very discreet because it looks like a jewelry accessory, and best of all: its battery lasts for 10 days!
On top of that as the band tracks how much you move, you can program it to remind you to move if you’re inactive for a while. This is very good for people like me who have sedentary jobs.
Another feature I like is that you can program your band to wake you up by vibrating: the band will figure out when is the best moment to wake you up according to your sleep cycle that day.
http://www.youtube.com/watch?v=GiC8QR_oHhk
Quantify Yourself
This kind of devices are part of an idea/movement called ‘Quantified Self’: a group of crazy people (in which I consider myself) collecting all sorts of data about their daily lives: anything from calories eaten and hours slept to steps taken or kms run. It started mainly as a way to measure fitness stuff but I’m sure it will evolve to measuring more mundane and more vain numbers. The basis of the quantified self is similar ‘Taylorism’ or ‘Scientific management’, the idea that you cannot improve things that you cannot measure. And being myself a Business Intelligence consultant, I know that is absolutely true!
Back to the UP band
I patiently waited for the UP band release date, November 6th 2011. Being in Canada doesn’t always make things easy, but this time I was happy: Jawbone said they were going to release it simultaneously with the States, and that you would be able to get it from your local Apple Store.
To make a long story short: I had to call 20 different Apple Stores, explain what an ‘Jawbone UP band’ is (and let me tell you that it is not easy!), and finally get one at the Eaton Centre’s Apple Store the very next day, Nov 7th. For this, of course I had to go to the store the very moment they told me over the phone that it was available and get the two sole bands they had for sale in my size. Basically, after just one customer they were left out of stock.
Good UP
And so I was very happy with my UP band! I registered it, used it with my iPhone, did my first work out and everything was fine in ‘up-band land’. The app still had its shortcomings: the food part is silly/useless and it only works on iPhone (I don’t care, I love my iPhone). You cannot get your data out of the phone (not even on a website) and there’s no way to post any of your information online. Seriously? We live in a social-media world, don’t you guys know that? If I run and post it on Facebook, is just to show it off to my friends!
I was so sold into the idea of “wearing it all times” that I showered with the band every morning. My fitness buddy (who is much more careful than I with tech stuff) took it off every time he showered and was also very attentive of not getting it wet. I laughed at his face: you luddite! Haven’t you see the ad where the guy emerges from a pool with the band on?
Bad, bad UP
Fate made me eat my own words: after five days of using my band and exposing it to the water in the shower, it was dead and my friend’s was alive and kicking. So I started googling and tweeting about this problem and found that I was not the only one with this problem. If you go to the Jawbone forums, you can read the horror stories of hundreds of people that were totally disappointed with the product. I tried to be a little more understanding because I really like the product, and so I asked for a replacement of my band. I called Jawbone on the phone, they were very nice to me and told me they were going to send me a replacement. After a couple of days waiting I got a new band that works fine!
Does it live UP to expectations?
I understand there are people still angry at Jawbone about the way they handled things. In Canada, we even had to even endure waiting more days to get bands and do the “Apple Store chase” to get one, so I totally understand that. Also, buying a half-baked product and paying full-baked price is not nice at all.
I’m most happy with the band: still think is a hell of an idea and a very good product. Maybe execution on the release could have been better (lot better) but I totally understand that sh*t happens.
After all the problems they had, I got a very nice email yesterday, pretty much admitting all of the issues they faced and saying they’re willing to fix them. So Jawbone is giving your money back for any of the bands you might already bought and stopping production until they sort their problems out. I think there is nothing else they can do to get you totally satisfied.
Their refund program is no-questions-asked. You can keep your band, return it, do whatever you like with it, they’re just giving your money back! You don’t even need a receipt so even if you got yours as a present, you can still get a refund if you’re not satisfied. That is what I call a very smart (as in intelligent and elegant) way of handling things.
Please, don’t go!
Its kind of sad to read they’re stopping their production and don’t even have a come-back date planned; that just gives me the idea that they’re probably not going to do the bands anymore. That would be really bad. Please Jawbone, do not do that. I respect that you need time to fix things up, but please do come back. I really think you have a great product and still want to recommend it to my friends and family!
Update
I received and cashed my refund for the UP band. I also ran into troubles with the first replacement band I already had (the vibration motor suddenly stopped working) but I called Jawbone and they sent me another replacement in less than 5 days. I cannot say more than gratitude words for this company, they are really exceeding my expectations as a customer and I intend to keep using the band for as long as I can to track all of my workout and daily activities.
Being the rebel that I am, I did project #8 before projects #6 and #7, so here are my impressions on #7.
Research your Topic objectives are:
Collect information about your topic from numerous sources.
Carefully support your points and opinions with specific facts: examples and illustrations gathered through research.
All of this is something that can be plain boring, are just there so recite some figures or data someone else created? Kind of being a news host? I think here the goal, as with any speech, is to find something you’re passionate about, or something you have a good understanding, and de-construct it to its bare essentials and then support those essentials with data.
You might think this is very difficult. One of the greatest things is that you can support practically any idea with statistics, and is pretty easy to find studies, often contradictory among themselves, that will help you state your point.
My speech was about food and how the people I know an I relate to it. I called it “We are what we eat”. I liked to use the title as a punch line somewhere in the speech, but this time I felt like that was being way too corny and skipped it. It worked well, as I didn’t feel corny at all when saying it (as I used to, so I know I would probably never do that again).
Since my breakthrough with Project #5, I’m feeling confident and I did last night presenting this speech. I felt totally on control of the audience, my eye control got much better and hand gestures felt much more under control.
This is the feedback I’ve got:
You know how to make any topic fun, even weight loss and portion control is engaging and interesting. Excellent energy! Great body language and eye contact. Keep working grammar and language. Sometimes you stumble on certain words and phrases. Great speech!
Very good speech. You collected lots of information!
Very interesting – well researched – well engaged – very confident – enjoyed it!
I could see a big improvement in your confidence! Good job and nice attention to detail
Excellent presentation skills: I like the way you move. You did your research – well done. Funny – works well with the audience. Data- appropriate for the topic / objectives of the speech. Tips: good idea. Good ending – perfect for the audience. You barely used notes
Well researched / Well presented. Just a few grammatical errors.
Loved the way you also referred to your scale to provide statistics, not just american studies. Lightened your speech which already was full of humour. Well presented in what could have been dry and boring but never was. Well done.
Great speech. Very well researched. Good humour and well prepared. Keep it up.
Very informative and well researched. You provided good examples about plate and portion sizes. Some vocal variety would have made your speech more impactful. Overall, well done.
Overall I think I did a good job, I got the point of the project was that you will always find information to help you make your point more valid. Presenting your ideas through other’s data and figures can make it your presentation more powerful.
I was planning a trip to visit my family and friends, so I had to go to the mall to get them some presents. I wanted to give them some simple but nice and simple things so I went to Aeropostale. I chose the items I liked and then straight to the cash register. I wasn’t surprised by the fact that the first thing the sales girl asked me was my email. I gave it to her, she just punched it into the register, scanned the items, I payed and that was it. Painlessly fast.
I later went to Gap to get some clothes for me. This one was even a little bit better. By the time I gave the sales girl my credit card she told me that they already had my email address and that they could send me the receipt there. I’m very good friend with electronic documents and I prefer them over paper all the time. So that’s how I got my receipt, just two seconds after I was out of the store my iPhone vibrated letting me know that I already had it.
How you do not ask for a customer’s email
I travelled to Buenos Aires a couple of weeks ago and was presented with the opportunity to deal with some more buying experiences. I had to get a keyboard for my mom’s computer, so I went to Compumundo, which is something like Best Buy in Argentina. The sales guy helped me pick the keyboard I needed, and then we moved to his computer to process the sale. He asked me all of my information (name, address, telephone number, postal code) for taxes purposes and then the email.
He started typing my email address (I was besides him so I could see everything he was doing). I noticed the application he was using was console mode (like in the old DOS days) and so I see how he couldn’t get to enter the ‘@’ symbol. One time, two times, three times. The ‘@’ was nowhere to be found. I was standing there for at least 90 seconds waiting for this guy to get his thing together, but it seemed like it was never going to happen. I tried to help him, suggested some alternative ways to enter the damn ‘@’. What annoyed me the most was that he couldn’t even get over the step where the system asked him for the email address. The system required him to put an email address. And not any email address, just something with an ‘@’ symbol. After seeing how frustrated he was, I suggested him getting some help from someone else. I could feel his embarrasement.
So another guy came, kind of making fun of “the guy that cannot type a simple ‘@'” and he typed in my email address. This is what he typed into the system:
the customer doesn’t@have an email address
You can clearly see that there is a ‘@’ in the middle, so the system was happy thinking it got a valid address.
What could have happened
I just imagine if this would have happened to someone that is not a social anthropologist like me. The guy would have tried two or three times to punch the email address, up to the point where the customer’s patience ends. The customer would have told the guy to put the keyboard where the sun doesn’t shine and went out of the store. End of story.
Consequences of this:
Customer gets annoyed, frustrated, angry. Doesn’t want to go to this store anymore. There are plenty of places where the customer can get his need satisfied.
Sales guy gets frustrated. He lost a sale, so he just lost money. And for something that wasn’t even his fault. He had to stand customer’s complain. To whom this guy would talk? HR? His boss? If this happens a couple of times, he would even consider switching jobs, given the case that he looses enough money out of this kind of nonsense.
The company looses money. The company have just lost a sale, and probably a customer for good, so even more money goes down the drain in potential sales. And what about if the company looses the sales guy? Wanna talk about money invested in the training and experience he got?
And all of this because just one guy, probably a programmer (nothing personal with programmers, I used to be one!), just thought and made the unconscious decision that forcing some validation on email address was good.
Customer experience is king
Customer experience, from beginning to end, is king in any kind of retail store. So it is very important that if you have some kind of retail store, you put someone in charge of this. Please validate the system, and by system I don’t mean the computers. Play the customer a couple of times. Do the mystery shopper thing. And please help yourself and your customers get things as easy as you can.
I presented yesterday my speech #6 at Toastmasters here in Toronto. Project #8 (yes, I skipped two, but nobody says you have to give them in order) is about getting comfortable with visual aids. I think the key here is to use something else than your voice to present a subject.
I like to talk about Lomography, which is a passion of mine. So I added up 2 and 2 and gave a visual presentation about a visual subject like analog photography.
I felt really comfortable, I used not only a powerpoint (which you might think is old and boring) but also some cameras to take pictures of the audience during my presentation. That was fun! I think everybody was really engaged and some people even asked me more details about the subject after I finished.
So, ladies and gentlemen, here is my presentation for your enjoyment….
Edit: if you wanna read the speech, click here. That will open the presentation in an external window, from there you can see the presentation and read the presenter notes, which are the part of the speech that go with every slide.
I feel that I’m really improving a lot on presentation skills… let me tell you something: Toastmasters Works! As with anything in life, you get better the more times you do the same thing over and over again, and presentations are not different in any aspect. I also have to say that my new found confidence might have to be with getting to know better the people in our group. So I will have to find a way to put myself out of the comfort zone and deliver in front of total strangers.
Steve Jobs passed away a couple of weeks ago and its biography, that was in the works for some time now, was released. I just finished reading it and enjoying it.
The first chapters about Steve’s childhood are good, and set up the ambiance for what comes next, a very interesting and rebel youth. All the middle part is what makes the book really valuable. The first Apple and ‘jail time’ at NeXT is very very good!
All the most recent times at Apple are well know history and there are not so many details you wouldn’t know if you’ve just been following the news all along. The last chapter could be a book on itself, it is an excellent summary of all of Steve Jobs’s values and it even has it in his own words.
The book is long and fun, some chapters are not so fun (probably his personal life wasn’t so exciting as his professional life) but it is very very easy to read. I would advice anyone to get a copy and read it, if you’re interested in recent technology’s history. It was very interesting to go in a travel through time and read about history so recent, and a cool way to remember.
One more thing, about Steve
I have a history with computers that goes back to my childhood, I started my career working with Microsoft and after many years I learned to discover and love Apple and its ‘think different’ more artistic approach. I still work with Microsoft technologies and feel really sad that they couldn’t learn much from Apple as they should have.
I feel deeply the loss of Steve Jobs as one of the great technology visionaries of the 20th and 21st centuries, and I think we’re gonna miss that industry guidance and path that Apple marked in the past years. Most of companies are not so daring and bold as Apple to innovate (Microsoft used to be but they lost that edge in the past years) so I really hope that someone can stand up to the challenge of being the next Steve Jobs.
A couple of days ago, as Steve Jobs passed away, I watched again Pirates of Sillicon Valley, the movie that tells the story of the first years at Apple and Microsoft.
It was good to remember that, at that time, Xerox and its PARC had enough budget to invest in R&D and let its engineers create crazy things like the mouse and the Graphical User Interface. They actually had so much money that they didn’t care about having them, as they were sure that the current status-quo was to last forever: computers were just a thing of the distant future, photocopiers are forever. And so along comes Apple, “borrows” the idea of the GUI and applies it to its Macintosh computer. And the Microsoft “borrows” that idea from Apple and Windows is born.
What if you change a couple of names and re-read that same story over ? In version 2.0
– Microsoft is the new Xerox
– Google is the new Microsoft
– Mobile is the new Personal Computer (Mobile as in smartphones and tablets)
– Apple is the new … Apple!
Microsoft has grown so out of proportions and so sure that PC and Windows kingdom were to last forever, that they had the luxury to ignore all of the money the invested in R&D to develop new products like the Tablet PC and Windows Mobile. And so came along Apple, “borrows” those ideas and applies them to its iOS platform (iPhone, iPad). And then Google “borrows” that idea from Apple and Android is born.
