By the end of 2013, 1.4 billion smartphones will be in use by consumers from around the world. Around 2015, Gartner predicts that more tablets will be sold than PCs worldwide and in 2017 1.75 tablets will be sold for every PC. The growth of smartphones is not only in the Western world. 75% of all new smartphones will be sold in Africa and Asia. The mobile era is upon us and this will require a different approach by organisation. What is the effect on big data and how can mobile big data add value to your organisation?
Mobile devices, meaning tablets, smartphones, smart watches and smart glasses, seem to have different guidelines than desktop computers. Although it is difficult to predict the behaviour on smart watches and smart glasses, the behaviour on tablets and smartphones is a good example.
The mobile revolution
Mobile devices are becoming faster every day and with that consumers are becoming less tolerant to waiting times on mobile devices. Nowadays consumers expect an answer on a mobile device in just three seconds. They can wait up to five seconds, but after that 74% abandons the website. Even more challenging is that 71% of mobile browsers expect web pages to load almost as quickly or faster as web pages on their desktop computers. This is regardless whether the user is on 3G or on WiFi.
Luckily telecom networks are improving and 4G is well underway in quite a few countries. It does take quite some time though before it is up-to-speed like 3G is at this moment. 5G is also coming and European Commissioner Neelie Kroes recently made € 50 million available to make Europe ready for the 5G era in 2020. However, as long as 4G is still relatively expensive and 5G is still far away, consumers will have to do with the slower 3G. Clear is however that data consumption will grow on mobile devices in the coming years. Ericson predicts that the average monthly data usages for smartphones will grow to 1.9 GB in 2018 compared to 450 mb in 2012. Tablets will grow to 2.7 GB compared to 600mb in 2012.
What is on-the-go big data?
So, what is mobile big data exactly? Basically it means making the results of big data analysis available on mobile devices. Of course, any proper analysis or number crunching cannot be done on a mobile devices, thus it is merely about giving consumers and organisations access on a mobile device to (visualized) results of analysis done somewhere else. This sounds simple, but it implies a lot of challenges.
Challenges of mobile big data
First of all, the upcoming trend of Bring Your Own Devices is a challenge for IT department in organisations. Especially in the BRIC countries, BYOD makes a significant uprise, with about 75% of employees in Brazil and Russia taking their own devices to work. IT departments are getting tired of supporting devices that they cannot manage or control. However, because it decreases costs for organisations and increases conveniences for employees, it is a trend that is hard to stop.
Several organisations such as Microsoft or IBM are reaching out to help by developing company platforms that can be used by the employees to securely download the necessary apps as well as secure the data that is transmitted. Organisations who want to make company results from big data analyses available on mobile devices of employees will have to ensure a high security level. In order to achieve that, organisations better start working as there is a lot to do. They should:
- Assess the employees who have access on a personal mobile device to the data;
- Document which data can be viewed via 3G/4G and which data can be viewed via secured WiFi;
- Train the employees in dealing with the data on their mobile devices and how to keep it secure;
- Create, document and communicate policies around how to use Bring Your Own Devices;
- Prepare your IT department for a plethora of questions related to all kinds of devices.
Secondly, the screen sizes are a lot smaller. It might be a retina display or full HD display, but it still is and will always remain a small screen (apart from a tablet of course). A small screen that is used on-the-go and in public areas. When the intelligent watches are coming (with a screen size of 128 x 128 pixels) or a Google Glass (with an expected display resolution of 640×360 pixels), this challenge becomes even bigger. This is of course not a problem, it only require a different approach though.
Thirdly, mobile devices do have keyboards (except again the smart watches or Google Glass), but typing on them is a hassle for a lot of people. Entering a query in a mobile big data dashboard thus becomes difficult and will take a lot of time. In addition, it is also prone to errors, resulting in unnecessary queries and data transmission.
The advantages of mobile big data
Well, with quite a few challenges, what are the advantages of on-the-go big data that validates spending time and money to overcome these challenges?
First of all, the availability of a large amount of sensors gives a lot of opportunities. There are numerous sensors in an iPhone and this will only increase in the coming years:
- The proximity sensor: which can determine how close an iPhone is to your face;
- The motion sensor / accelerometer: enables the iPhone to automatically switch between landscape and portrait;
- Ambient light sensor: determines the amount of available light in a space;
- Moisture sensor: which detects whether an iPhone has been submerged in water;
- A three-axis gyroscope: which enhances the perception how the iPhone is moved;
- A magnetometer: measures the strength and/or direction of the magnetic field in the vicinity of the device;
- GPS sensor: determines the location of the iPhone.
These sensors can help to increase the effectiveness of the visualizations shown on mobile devices. It can provide effects and tools not available on desktop computers and therefore increase insights into the big data. When developing a big data startup or a big data strategy, it is therefore wise to take on-the-go big data into account and make the most of the sensors present in mobile devices.
Secondly, mobile devices simply make it possible to have access to all your data at any time and anywhere. This will increase employee productivity, because a warehouse employee for example has all necessary data on his or her tablet instead of having to walk back and forth to a desktop computer with that information. Also in the health industry it can provide a lot of value. A doctor that has all available data about a patient while standing at the bed of the patient can save extremely valuable time and even save lives. It can ensure that all doctors have the same, correct, information available on their mobile devices at all time, anywhere.
A third advantage of on-the-go big data is the availability of push messages that allow real-time data analysis to have the most effect. Whenever an event is triggered by data analysis it can be pushed to the users via the mobile devices. This can result in immediate action, while desktop computers require the users to be behind a desk. If the mobile device also allows the user to respond immediately, the efficiency as well perhaps customer satisfaction will increase.
Four on-the-go big data guidelines
In order to be successful with on-the-go big data, organisations should take into account four guidelines. These guidelines will help organisations make the most of their mobile big data strategy:
1) Use simple but smart visualizations
Although the smaller screens of mobile devices require a different approach, the large amount of sensors in the mobile devices allow smart visualizations. Organisations should remember that on a small screen only the most vital information should be shown, as too much information will confuse the user. Especially on tiny screens like the watch or the glasses this is even more important. Give the user the vital information first, but also give the opportunity to dive deeper if wanted. Remember to limit the steps needed by the user to find more information; a small screen is not suitable for a lot of different steps.
2) Enable voice recognition
The mobile big data dashboard should recognize voice input. Google Glasses as well as smart watches do not even have a keyboard anymore and focus almost solely on voice recognition. Even smartphones and tablets are not suitable for entering a (large) query with a keyboard, as that is generally a hassle. If possible integrate the mobile big data dashboard with existing programs such as Apple’s Siri. Users are familiar with Siri and it already consists of sophisticated voice recognition software.
3) Ensure fast loading of visualizations
Users expect a mobile device to work lightning fast. Complex data analyses are done in the cloud and the results are returned to the mobile device. Take this into account when giving the user the ability to view big data visualizations on their mobile device while on 3G network. Data intensive tasks could drain a monthly data subscription plan easily, while the user becomes frustrated. Focus on the most important analyses that a user needs to be able to perform while on 3G and allow the rest of the analyses and visualizations to work only on WiFi.
4) Secure your data transmission
Only 4% of the smartphones are protected with security software. On-the-go big data will require giving mobile devices access to (sensitive) data results. Determine which data is sensitive and ensure that this data can only be transmitted when the user has a secure and acknowledged WiFi connection. Especially in health organisations sensitive data should not be used on public WiFi or 3G/4G networks. The data that is only available via WiFi should also be available offline, so that if needed an employee can continue to work even when there is no WiFi or 3G/4G connection.
The future of on-the-go big data
The future of mobile big data is difficult to see as we are at the brink of a mobile revolution. According to Nathaniel Mott, the future of computing will be a question of head vs wrist instead of desktop vs mobile. The coming years we will probably be flooded with new mobile devices currently unknown and all of them will require a different approach of on-the-go big data. So the challenge ahead for organisations is to accept this and adapt on time to meet the needs of the mobile future.