As indicated by Mobile Data Traffic Forecast by device – An exploration by CISCO, cell phones are turning into the most utilized method for producing traffic. This movement is viewed as high for the most part on account of the utilization of mobile applications or mobile surfing too. Also, the research showed that by 2017, the information generation grew 50 times over, as compared to what it was before.
‘Data-driven’ is a keyword in describing all processes and products of the current digital age. Most companies of this era strive to be data-driven. Thus, numerous businesses which are into developing mobile applications, particularly iPhone apps, integrate data analytics software and concepts into their products & services.
As companies and their user bases grow steadily with time, they have to be ready to handle massive influxes of data caused due to the usage and presence of mobile applications. Each device is connected to the web via the Internet and this serves as the medium for streaming massive amounts of data. Big data is generated from a variety of sources that include customer logs, social media interactions, web traffic logs, online videos and many others.
All of this data can be unstructured, structured or semi-structured in nature. It needs to be cleaned and broken down for analysis so that the companies can reach unprecedented growths.
The era of iPhone is here to stay and there is a rush for being the ones who extract and use big data and analytics solutions in iPhone apps. Many companies have moved into developing iPhone Apps that can handle big data such that they can keep up with their competition and meet the huge market demand.
The Relation between Big Data and Mobile
With a rise in the number of mobile phone devices being used, businesses are investing more funds than ever in the development of apps with mobility. These devices or smartphones are responsible for the major amount of the traffic and data generated. Thus, a new term is in vogue; Mobile Big data.
Technically, the only difference between mobile big data and the data created from a traditional website is that smartphones, which are the source of mobile big data, are becoming the most widely opted for as a medium to perform the same operations as a website, but in a more convenient and quicker way.
Personalized and optimized apps track the user’s searches and frequently used data to provide the optimum solution to a problem. These apps can be installed on the smartphones and can also be connected to different wearable devices. This data is accumulated and then used for analysis to provide the user with the required information or solution.
Some popular apps that make use of Big data in functioning areSiri,Roambi, various Fitness apps and Travel apps. Big Data is said to be the longest lasting technology in this fast-paced industry and the most feasible step for a Mobile application is to opt for it as the back-end.
Tips for Creating Big Data-driven Backend for an iPhone Application
As virtual architecture is considered apt for managing big sets of mobile data, organizations have to look for a solution that enables them to focus on the valuable insights hidden in the datasets, rather than addressing infrastructure concerns, like storage capacity and elasticity and costs. Many companies have taken to the cloud to avoid these problems.
For instance, Apple gives registering and effective solutions and cloud-based capacity for both, business and customer utilization. They acquired FoundationDB, which is a prevalent restrictive database engineering that is utilized broadly for big data applications.
Virtual engineering is ideal for overseeing a lot of portable information. With this, organizations must bet on it and utilize it further bolstering their good fortune. A few hints for making a Big data-driven backend for an iPhone application are:
1. Invest aggressively in Cloud Computing and Storage:
The current era of Mobile app development organizations has embraced analytics and drive the current data volume surge. Thus, they are in great need of robust IT infrastructure to handle large amounts of data.
The organizations in question must analyze the pros and cons of owning and maintaining a dedicated data infrastructure. Cloud Storage minimizes capital expenses, critical results timelines and the rate of risks.
2. Real-time querying by analyzing data at collection points:
Large data sets make it difficult and time-consuming to obtain any valuable insights from them due to their sheer size. In order to streamline this process, iPhone application developers use real-time querying.
Querying engines are used by organizations to optimize and add interactive queries on data sources. This enables an accelerated process of deriving valuable insights from the data.
3. Agility and Flexibility:
Cloud provides a certain level of flexibility that an organization needs with the changing business world and increasing demand for products and services. It can also become difficult for developers to cope with the increasing market demand and competition.
With the increase in the level of technology, Cloud is capable of adapting and delivering optimum solutions. It enables the business to scale according to its needs and invest only the resources which are important at the particular time.
A Mobile phone is an ever-present device in the hands of every individual, be it young or old. As of January 2017, there were around 2.2 million apps in the Apple App Store all over the world. iPhone apps and devices target the personal interests, needs and behaviors of the users.
When the information obtained from users is analyzed in real-time, it serves as a powerful treasure trove of knowledge and predictive analytics techniques can be applied in order to extract valuable insights relating to consumer behavior. These insights can then be used for the right kind of marketing and to gain a competitive advantage. This is how Big data fuels iPhone apps.
