Huge Data!

The new iPhone 5 – yet another James Bond to collect Big Data?

Congratulations to all iPhone lovers and owners with the launch of the new iPhone 5 (5c and 5s) and also iOS7. I have installed the iOS7 on my iPhone 4 recently and like it so far. It is nice, and has furnished most of the former features like visual-touch screen effects and software convenience. It is topped with additional sound effects and ringtones as well as a few other slight improvements. Here is an external link to a video describing what is new in the new iOS7:

Another feature that caught my attention was the camera roll nuances. In the older version along with the photo albums there was a map with locations of where the pictures were taken, if you activated the location services. In new iOS7 it is time-stamped and indicates the location of the photo as well. You have an option to collate your pictures by the moments taken as well as by the locations. On the full scale map you see your stacks of pictures by locations and the screen of the phone lets you zoom in to see the exact location where the picture was taken with 2-3 meters maximum possible error. On the one hand this is an amazing option, but on the other hand, if the iPhone knows it, then Mr. Tim Cook and his intelligent employees know this information for sure, too. And you don’t know how large and ongoing that spiral of flow is. So iPhone makers have the meta data of where you shoot pictures and when you do it. But I am wondering, is it possible that they also see the content of the pictures???

Fashionable Big Data: The “it” Trend

I’m really into fashion, love following blogs, using Instagram and Tumblr to know the new trends and get inspired by new ideas.  After reading a case study about Burberry, for my marketing class, and discovering that this 157 year old brand has evolved and adapted to keep up with most of the new technology without loosing its essence (please refer to artofthetrench.com and see what I mean), I started to wonder about the connection between Big Data and Fashion and how the fashion industry could be related with the new “It” trend of technology?

As we already know, Big Data (BD) can help us gain insights to improve already existing products and services or to create new ones.  Lately this hasn’t been a mystery to fashion designers and trendy retail stores, that’s why these two are using information to understand what the customer wants and additionally get a financial benefit out of it by optimizing production and by minimizing the leftovers of garments. How? By hiring companies such as Bodymetrics, that collects data about body measurements and sizes and gives this statistics to the designer and retailer to better predict the demand of their products according to how many items of a certain size are sold.

Another way in which BD is improving the fashion business is trough social media, in this case the information gathered from Facebook, Pinterest, Polyvore, Instagram, and other social websites can help to figure out consumer sentiments towards a certain brand or product, which is essential feedback for retailers and designers and avoids them from relying exclusively on post-experience or intuition. 

Now that we have a clearer perspective about how the fashion industry and Big Data are linked, we can confirm that this is a match made in heaven. And can ones more ratify that BD is improving everything around it, so tell me what’s not to LOVE about BIG DATA?

iData?!...

In the line of the latest development of smartphones and tablets, we have witnessed the explosive development and sales of applications for the mobiles. These applications contain loads and loads of information as well as entertainment tools. If smart phones are that smart, could they carry and analyze Big Data?  

Yes, they can!

Nowadays our smart friends can carry and analyze big data on the spot. The new, for then, application of finding and scanning bar codes or QR codes is not a surprise for anybody today. This application contains and recognizes information from tons of products listed on the Internet.  You can easily get price quotes for any book or perfume with a bar code, or decipher any message loaded onto the QR code on any promo or ad. 

Not only app developers pile data for us, but the new trend in mobile Big Data applications is, they are becoming based more and more on UGC - user generated content. For example, Waze – a free GPS navigation application in the AppStore caught my attention when I first met its co-founder – Uri Levine as guest speaker in Venture Lab Competition day at IE. You open the application on your phone before driving your car to the bar on the weekend and immediately become a contributor of the application and are notched by the program. It was gradually making sense to me, how a user generated system was gaining such popularity and it eventually clicked the button when I read in the news about the sale of the Waze to Google for 1.3 billion (yes, billion) US dollars only 6 years after its establishment.

Cloud computing and data warehouses is another application of Big Data and its use in mobile apps has created controversial rumors about leakage or even “legal” delivery of private information contained in clouds to the application developers. Recently the information security issues has brought a higher attention onto the developers and put the security issues on demand. 

So with growing loads of information and Big Data, life and business solutions are being made easier, but the security and safety of the information have become an issue meanwhile. Make sure you keep your very private information really private!

Big Data Stats!!!!!!!!

Big data – a journey 90 years back

Big data – a journey 90 years back

Some weeks ago, when I was in a hotel in South East Asia just about getting ready to check-out, the TV was still on and the movie J. Edgar, directed by Clint Eastwood was being shown. Leonardo DiCaprio stars in the move as J. Edgar Hoover, the powerful head of the FBI for nearly 50 years. There is a scene pretty early in the movie when J. Edgar Hoover is fighting for more competences for the Bureau, which so far has not been granted any teeth. All his passion goes into fighting and solving crimes. Maybe the most important weapon in his view is central access to data. For instance, he fought for a centralization of nationwide available fingerprints.

Just a few scenes after the hearing, you can see J. Edgar Hoover in the FBI premises when huge loads of finger print files arrive. This was just a first step and shortly thereafter an identification unit was formed. This all happened in as early as 1924 – almost 90 years ago.

To me this is an early example of big data. No internet, no satellite communication, no computers, not even copy machines as we know them today existed at that time. Can you imagine the amount of data in physical paper that was collected with the fingerprint files in just one location? However, this kind of data volume would probably fit on just one server blade of today’s computing centers. We can consider this as one of the early examples of big data, however, not in any way comparable with the data amounts collected nowadays – whether by corporations about their customers or state authority based on whatever motive. By current standards this kind of data collection would not even be considered “small data”…

The next problem after the collection of the data, is analytics and data mining. There was no electronic index and you can find the right data just with three key words or two mouse clicks. A sophisticated filing system had to be in place to enable agents to work with the fingerprints. Frankly speaking, for a non-expert like me, it sounds incredible how they worked on comparing finger prints from a crime scene with file data in their archives.

Within a short period of time from some feared bureaucratic organization the FBI has been transformed into a highly respected agency based on this new approach of fighting crime. Data collection and development of new techniques in crime scene investigation represented key factors for the success of the agency. Today, the FBI employs more than 36,000 special agents and support professionals, overseeing a budget of more than 8 billion US dollars. Besides its US operations, the FBI now runs field offices around the world.

Watch the trailer of “J. Edgar” (2011) on IMDB: http://www.imdb.com/title/tt1616195/?ref_=fn_al_tt_1

How our future cars will be like?

The present day car is full of sensors, controllers and electronic control units. The user interface includes, for instance, instrument panel, on-board diagnostics, user controls and settings and in car entertainment systems. Once you are inside the car you are in a different world. What once felt more like a couch, which was accidentally equipped with a steering wheel and pedals, now looks more like an airplane cockpit. Everything is interconnected in our world of devices and gadgets, the car seems to have been unfortunately left out. The only time when detailed vehicle data can be accessed is when it visits the workshop.

This presents a unique opportunity for manufacturers to start connecting car to the internet. This will enable capturing real-time data on car usage and performance. The Big data can be mined to provide insights into cars performance and customer behaviors. Manufacturers may find the costs of connecting the cars prohibitive, but the benefits do make a strong argument in favor. Some premium manufacturers are already offering online connection packages as extra for their cars.

Connected cars: Real-time access of vehicle data can revolutionize the mobility for passengers. The experience of moving from one place to another can be improved in a connected car. The cars performance can be customized based on the route chosen to travel. The suspension, the power, the steering, the transmission, the tyre etc. can be optimized based on real-time data of the location of the car, weather and the type of road. The goal of such optimization can be to improve comfort, performance or fuel economy.

The user driving habits can be mapped on real-time and necessary advice on improving the driving can be suggested. This driving data can be analyzed to predict life of various components or time to go for repair. It can be used to predict failures and provide alerts on possible breakdowns.

Cars can be connected to share information to each other while on road. This communication between cars can share information like if brakes are being pressed, if a driver has fallen asleep, if car tyres are slipping or skidding or if the cars are too close to each other. Data from other cars can be used to predict behavior of other cars or drivers on the road.

Customized cars: Such real-time data can be used for analysis to find trends and insights into driver preferences and habits. This data on the interaction between the driver and the car can be used to design and optimize various features and components of the car. A feature seldom used may be removed and a component used more frequently may be improved for performance and reliability.

Past history of driving habits and preferences of a customer could be used to develop a car customized to match person’s needs. The data on habits may also help, for instance, to optimize gasoline consumption by choosing the right engine as well as personalized engine management. Such a customized and optimized car would deliver more value for customer and also lead to lower costs to manufacturer but eliminating features or equipment not desired by the customer.

Safety: Historical data on driving habits can be used to predict accidents, areas prone to accidents, conditions leading to accidents or possible errors a user can make while driving. Real-time information on road conditions, weather and accident history can also significantly improve road safety. Driving will become a lot safer. Car insurance rates could be more accurately determined with driving behavior and history of the customer. Another benefit of safer road travel will make the host of safety equipment like anti-lock braking systems, electronic brake force distribution, electronic stability programs and airbags etc may become redundant, making cars a lot cheaper.

Know more: The locations were the car is parked can provide further insight into customer’s life. This data can be a gold mine for marketers. This information can be used to position various kinds of products like hotels, holiday trips, shopping malls, lifestyle products or services etc. Some may find it intrusive to their privacy. But location data can be used to enhance driving experience. Customers profile and historical preferences can be used to suggest thing that a customer may find interesting on route.

Manufacturers who collect and have therefore access to such data will be in a superior position compared to those who don’t. The intimate knowledge about its customers with the help of big data can help manufacturers to build a stronger relationship with customers by delivering value desired by the customer and exceeding customer expectations by accurately predicting their behavior.