Big Data Analytics and Mobile Apps
Big Data and Mobility are two major verticals of Digital Technologies. However they are no more two different verticals but continuously intersecting each other . While defining Mobility ,Big Data road maps it is important both verticals address the requirement of other vertical . It is also important to understand how each one can leverage each other.
How Big Data impacted by Mobile Apps
- One of the biggest source of data is now mobile Apps . As the smartphone and mobile app penetration is continuously growing – volume, variety and velocity of data coming from mobile apps is continuously increasing . As the Apple and Google continually upgrading and offering new features in every OS version releases it is important to have a big data architecture addressing mobile app data source
- IOT and Bluetooth enabled devices – Android and IOS in their recent releases uses mobile devices to interact with external sensors and devices . Lot of IOT projects develop app which interacts with mobile apps . Collecting and analyzing this data is a critical part for the projects
- Mobile Analytics give much more deeper insights about users behavior , demographic , Location etc . Big data Analytics can use this data to generate user based reports . For example certain app users location analytics can help planning of campaigns in certain location in specific duration .
How Mobile Apps can Leverage Big Data
Mobile app strategy of presenting the content , data ,offenders ,deals by simply fetching from backend is no more relevant . A right mobile app strategy should be focusing on presenting the right content to right people in an effective manner . In order to achieve this mobile app should implement a Big data strategy and utilize machine learning algorithms to contentiously improve based on user behavior and patters . Also lot of mobile app rely on external data sources to understand trends and current hot topics to present the relevant content to users
Analyzing mobile data will also help on various departments . For example if mobile analytics can give information about what is the product most people are interested . This information can be used to manage supply chain ,pricing etc
Introduction big data also bringing lot of new plugins and tools which were considered complex and costly before . For example there are lot of open source products for image recognition , face recognition , related product mappings , sentimental analysis etc can be integrated with mobile app with lesser efforts .
What are the challenges
Mobile developers are constantly challenged with wide verity of tools and technologies they need to adopt for a mobile app development . Unlike before android ,ios programming skills are not just enough to complete a mobile app . Good understanding of various tools and cloud ecosystems is required to complete a mobile app project now . Cost involved on each tools and cloud solutions are another challenge .
This was the one of the main reason gizmeon introduced interbeeps (https://gizmeon.com) combining many of the digital and mobile analytics capabilities which can be easily integrated with mobile apps with lower initial investment