Technology industry has been evolving continuously since its inception. The evolution was hastened by the commercialization of “Internet” in 1995, making internet publicly available for everyone. Rapid expansion of internet in all the continents saw a major behavioral change in the community. There was an era of well-informed and resourceful users, who knew the power of information. This trend never stopped and has now given way to three major trends which are adding to the old wave of internet.
Let’s start with a simple definition of Cloud computing as given in the bible of modern World, the Wikkipedia.
“Cloud computing is the delivery of computing as a service rather than a product, whereby shared resources, software, and information are provided to computers and other devices as a metered service over a network (typically the Internet)”
In simpler words, Cloud computing is a way of eradicating the need of costly infrastructure necessary for any IT business venture to survive and expand. So, an organization can start benefitting from the IT services right from the word go.
Visualize an example of every individual in the city generating in-house electricity for solving individual electricity problems compared to the central regulatory authority producing electricity at one common place and then supplying it to every household and billing them accordingly. The concept of cloud computing is somewhat similar. Providers, all over the World, are setting up their infrastructure for providing computing power to individual users or small medium organizations in order to satisfy their demands, and charging them nominally for the services used.
Now imagine if you have set up a new organization, and you just started its website. The website is hosted on a server which you bought for your organization. As the traffic on your website increases, your website slows down, and you need to have additional servers to maintain the user experience. This is an expensive and time consuming process, and when traffic is low, you still need to maintain the servers, thus incurring huge maintenance costs for the company. This is where cloud computing can deliver the edge. Instead of buying and maintaining new web-servers, you can now put your website on the web-server online, and instantly scale up or down the capacity and computing power, without having to invest in the actual infrastructure.
You don’t need to be a creative genius to understand the benefits of this concept. One non-evident benefit can be reduced carbon emission per server. Below are the popular models of Cloud Computing and their key benefits.
- Infrastructure as a Service (IaaS) – Allows applications to run online on the provider’s hardware. This means that your existing applications over your Data Centre can now be migrated to cloud and maintained from there only. Amazon’s EC2 is a popular example of IaaS.
- Platform as a Service (PaaS) – This model allows the users to create their own applications, for example Google provides “App engine”, and Microsoft provides “azure”, Salesforce offers “Force.com” which allow users to create new applications in a rapid and low cost manner. This is the perfect tool for developers to build applications and host them almost instantaneously without the hardware hassles.
- Software as a Service (SaaS) – This model is generally used by application or product based companies who can offer their service on a “Pay per User” model. SaaS is the way to consume off-the-shelf applications over the internet. For example, Google docs, application which provides the flexibility to you and your co-workers to work on the same documents while based out of any location, work on any machine, and independent of time constraints. Online office is powerful software offered over the cloud by Microsoft. So, you don’t need to buy those expensive licenses, instead you can simply register your number of users, and pay as they access office online. Clarizon’s online project management tools and Salesforce’s customer relationship management tools are other popular resources in this segment.
- Device and Location Independence: With globalization and outsourcing, companies need their employees to be available at the time that might be the best in their local region, or may want them to login from the devices that are not necessarily on their office desktop. Bottom line is that the employee may have to access that critical information from anywhere on any device. While conventional client-server models might be restricted to provide such a solution, Cloud computing aces in enabling such a freedom of access.
- Cost Advantage: As explained in the above examples, an organization may have to buy more servers, to ensure a good user experience. But, imagine that the traffic on that website dried all of a sudden. What will happen to the newly added server? Who will bear the cost of maintaining that server? To address these issues, cloud computing gives the cost advantage, by charging the customers only for the services used, with Pay per User model. This substantially adds to the cost savings of the organization, and provides flexibility to young entrepreneurs to venture without worrying about the cost of Infrastructure.
- Performance: User experience is directly proportional to the processing capacity of your servers. The better the processing capacity, the better the performance. But, how expensive is it to consistently provide the same user experience? I would say very expensive, specially having a server for, let’s say, 100 users. Again, if the number of users increases exponentially, maintaining the performance will be very expensive. Hence, Cloud computing provides the optimum mix of cost and performance.
- Scalability: As seen in the above models, Cloud computing makes certain that processing power, storage capacity and other resources can be immediately scaled up or down. This is an important aspect in today’s business environment as users are connected 24×7 to your servers, and organizations do not have the time to keep their websites down for couple of hours and increase their server power. Also, with ever increasing internet population, young entrepreneurs (and SMEs) can’t be sure of the server capacities which can guarantee a consistent bandwidth and other necessary resources.
- Privacy: How comfortable would your customer be, if you tell him that his personal information is not in your database but on cloud of external vendor? Also, this information might be sold to some advertising or Data Analytics Company for money and you may start receiving Credit card and loan calls. Thus, a common regulation needs to be in place before signing up for Cloud Computing.
- Security: Thinking from hacker’s point of view, in order to gain access to the confidential information of 20 different companies, he does not need to breach the security of 20 different companies, but instead just one place.
- Vendor Restriction: There are constraints on languages and tools when you use platform as a service model. This means that if you have built your application on Azure, then you cannot run that application anywhere other than on Microsoft platform.
Again starting with the simple definition of Big Data as given by Wikipedia:
“Big data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.”
The image below shows the plotting of structured vs. unstructured data against persistent data vs. Real-time streams of data generated via social media.
Marketers have always complained about how the product is not good enough to attract the customers. Is that the truth? Were they targeting the right audience? Was marketing budget spent on the right activities? How does one estimate the effectiveness of marketing campaigns? What will be the next purchase of my customer?
All these questions were answered by the technology called Predictive Analytics, which was feasible because of information. But, where does this information come from? The answer is pretty straight forward. Yes, you are bang on! It is the social networking and e-commerce websites like LinkedIn, Amazon, Facebook, Google and many more. In short, any activity of your potential customer is recorded and stored in a relational database, on which the predictive analysis is done. The heaps of data are analyzed like customer demographics, age, location, gender and even behavior like which websites he’s visiting, which products he’s checking, his online spending pattern, that help you predict the right offers for the customer, at the right time.
Have you recently thought of purchasing a mountain bike, and all of a sudden, while browsing through websites, you see a banner trying to sell you one. This is the power of “Predictive Analytics”. Figure 3 describes the MAP framework used for Predictive Analytics. Further details on the process of Predictive Analytics are beyond the scope of this study.
Similar to Cloud Computing, Predictive Analytics is also finding its role in various industries like e-commerce, financial services, insurance, retail, pharmaceutical, healthcare, media, technology and telecom. If I consider horizontals, then marketing, supply chain, and risk analytics are the areas where Predictive analytics is most commonly used. Three key models currently used are:
- Predictive Models: As the name suggests, this is the model used to predict the customer’s future behavior. This model takes past activities of the user as the feed, along with the live transactions of the user, and come up with the human simulation in that situation. This is finding its use extensively in fraud management and marketing.
- Descriptive Models: Descriptive models can be seen as a means to segment the customers based on their attributes like demographics, age, gender, product preferences etc. This model tries to use relationship between product and consumer and then classifies consumers into groups. Like a consumer buying baby diapers will also be interested in buying baby milk powder etc. So, a category is made and this customer will be placed in this category.
- Decision Models: This model collates all the other models and information and predicts the result of decisions involving multiple variables. Past, present and predicted data is used as an input, generating the outcomes for multiple scenarios. The model is finalized through a three stage process starting from formulation, followed by evaluation and finally appraisal of the given model.
- Personalized sales almost real-time: In today’s connected environment, customers demand the right offers not only at the right time, but via channels like social media, mobiles, online, email etc. So, as a marketer, you can no longer wait for him to pass through the billboard and read your campaign. You need to do it instantaneously, right when they are reading those articles or browsing the net to make his next purchase.
- Measurement of marketing campaigns: Traditional marketers often found themselves in a fix when asked about “How successful was the marketing campaign?” Not anymore! With interactions becoming more and more personalized, marketers now instantaneously know “Which campaign drove the online purchase?” This makes it relatively easy for the marketers to gauge the success of their campaigns and quantify the returns.
- Identifying the latest trends: Imagine you are to launch a new product, in which you have invested millions. What is the right time to launch? What is the right price for your product? With predictive analytics, you can follow the trends and easily decide the optimum time of launch and price point for the product.
- Processing Capacity: Big Data ranges from few dozen terabytes to many petabytes of data in a single data set. All organizations do not have the processing capacity for handling this humongous amount of data. Even the companies operating in this arena are facing difficulties in maintaining the capacity to process this data.
- Contextualization of Big Data: Data collected cannot be simply used or mean anything unless you know the context. For example, you accidentally visit a mountain biking website, and from then on you start receiving mountain bike ads, when you had no interest in buying one. This is the biggest challenge that the Big Data analytic companies are facing today.
Smart-phones and tablets
Preserving the sanctity of the article, let’s start this trend by some definitions.
“A smart-phone is a mobile phone built on a mobile computing platform, with more advanced computing ability and connectivity than a featured phone.”
“A tablet computer, or a tablet, is a mobile computer, larger than a mobile phone or a personal digital assistant, integrated into a flat touch screen and primarily operated by touching the screen rather than using a physical keyboard.
Onset of this wave of technology was identified by “Popular magazine” in 1999, quoting Ericsson R380 Smart-phone to be most important advances in the field of science and technology. What happened afterwards, how iPod touch paved way for iPhone which prepared the customers for iPad is just history. Figure 4 shows the usage patterns of Mobile and tablet users. Take a look!
The concept of smart-phones and tablets started in late 19th century with players like Ericsson, Nokia, HP and Microsoft investing billions to create this technologically advanced market. Studded with email, web browsing, Wi-Fi, Camera and many other features, smart-phones started a behavioral shift. Though many players tried their hands in this market, none could do it the way Apple did. In 2007, Steve Jobs, with his ace product, “The iPhone”, also branded as the most innovative product in the history of technology, gave users an experience of multi-touch interface, with a large enough screen which removed the need of complimentary devices like Stylus, Keyboard etc. This new way of interacting with technology, along with the support for third party “web 2.0 applications” saw a huge tide of content/ application developers for iOS. Strategically formed App Store, provided a one stop shop for buying applications, closing all the loose ends and creating a strong Apple ecosystem. Starting with mere 500 applications, today App Store has more than 5 million applications, and increasing.
Soon, other players, like Samsung, HTC, and Nokia realized the potential and started to target this market. But, why did it become inevitable for these players to be present in this industry? What was the urgency?
The answer is clear, the behavioral shift! People wanted to stay connected all the time, to access news on the fly, to share it with their friends and families, to make informed decisions about the commodity they were buying, and much more. It’s the thought process that has changed.
The following are the top three operating systems that have been the drivers of this paradigm shift:
- iOS: This is the platform on which Apple runs its products. Basically it is a Unix-like operating system supporting data manipulation and multi-touch gestures, built in C and C++. iOS currently has 26% of market share and is the 3rd most used OS in smart-phone/tablets category.
- Android: This is the most popular OS in the market with close to 50% market share. Such high market penetration can be attributed to the fact that Android is based an open-source model. With close to 4 million applications, Android has successfully created its own ecosystem.
- Windows 7.5: Since, Nokia and Microsoft could not come up with the right products at the right time Nokia lost majority of Mobile market share to Samsung, Apple and HTC. Now, Nokia has paired up with Microsoft that has come up with a platform for Nokia’s new range of smart-phones. How successful will this partnership will be? I guess we have to just wait and watch.
In today’s era of globalization, staying connected is inevitable. Smart-phones and tablets are aiding this new human need for information and socializing.
- Connectivity: With advancements in technology like 4g spectrum, Web 2.0, these smart devices help us in remaining connected with the world 24X7.
- Mobility: Strong battery backup and almost negligible weight makes it convenient to carry these devices, enabling the network accessibility on the fly.
- Ease of Access: One touch operations, speech commands and image recognition facilities have made the use of these devices so simple that people of all age groups are hinged to these super powerful yet simple to use machines.
- Expensive: Top end models of these devices are still very expensive, and are away from common man’s reach. There have been some local technology advancements but still to make it available to all will take some more time.
- Delicate: The lighter these devices are, the more prone they are to physical damages. In order to keep these devices light, companies are missing out on the physical robustness. Take an example of Xperia Arc or an iPhone. A callous drop on the floor can shatter these machines into pieces.
To conclude the article, I would say, the trends/technologies mentioned above are important not because companies are making billions out of them, but because these are alluring a paradigm change in how information is generated, analyzed and consumed by the users and organizations. Companies that were not bothered by consumer’s activities are now paying close attention to every move of the user. They don’t want to repeat another Nokia blunder! Don’t be surprised if I tell you that Google or Facebook knows more about you than some of your closest friends. What, where, when, how and why are the circle of questions that need to be addressed when we think about Data or I should say Information! Choice is yours! Are you ready to shake hands with the future and get on the power of Cloud!