Introduction to Big Data: Interesting Statistics, Facts, and Figures

by Anshul Sharma Top Mobile App Development Company In UK

Today we focus on our phones, mobile apps to execute multiple tasks, such as activity tracker, diet manager, appointment planner and more. All of these applications require the extensive use of data, which a comprehensive data management application has to evaluate. Big Data administration helps get insights from the apps created knowledge that consumers use every day. The rapid growth of the data helps the app developers at Fluper a mobile app development company in England to use the insights to drive and make it a success. The Big Data platform powers the process of mobile app development to enhance user experience.

What is Big Data?

Big Data is also a data but of enormous size. Big Data is a term used to describe a set of data that is small in scale which expands exponentially over time. In short, this data is so large and complex that it cannot be handled or analyzed effectively by any of the conventional data management tools or process it effectively. It inundates day-to-day management. But what is relevant isn't the amount of data. It's what the companies do with important data. Big data can be mined for insights leading to better business decisions and strategic moves.

Types of Big Data

Big Data could be found in three forms:

1.Structured

2.Unstructured

3.Semi-Structured

1. Structured Data:

Every data that can be stored, viewed, and interpreted in a fixed format is considered' structured' data. Over time, computer science expertise has been more active in creating methods for dealing with and deriving interest from such data (where the format is well defined in advance). But nowadays, when a scale of such data expands to a huge extent, traditional sizes are in the range of several zettabytes, we are forecasting problems.

2. Unstructured Data:

Any unexplained type or structure data is labeled as unstructured data. Apart from the enormous size, unstructured data faces multiple challenges in its analysis to extract meaning from it. A typical example of unstructured data is a heterogeneous source of data that contains a mixture of simple text files, photographs, videos etc. Nowadays, companies have plenty of data available for them, but sadly they don't know how to extract meaning from it as it is in its raw form or unstructured format.

3. Semi-Structured Data:

Semi-structured data may contain data in both ways. We can see semi-structured data as structured in form but it is not specifically defined in relational DBMS with e.g. a table description. Semi-structured data, for example, is a data described in an XML format.

How Big Data can play a major role in mobile app development?

Big data plays an important role in mobile app development in many ways:

1. Understanding Customer Needs:

The vast amount of data that consumers produce on a regular basis can be processed using big data and transformed into useful insights. Through understanding how people from different backgrounds, age groups, behaviors, and geographies connect, respond, and engage with mobile apps, you are able to formulate ideas for new and creative features and improve current app capabilities.

2. Drive User Experience Analysis:

Using big data, you can do a detailed analysis of user experience, get a holistic 360-degree view of usability and user interaction, analyze the feedback for each app or website, and assess the most sought-after features as well as pain points. You should consider the elements of your mobile app that make users spend more time and encourage them to leave. Then you can use this information to create a list of the very things that users need, plan for design changes or adjustments, enhance user experience and optimize interaction.

3. Get Access to Real-time Data:

Big data helps to keep up with the times a lot. You will take real-time, data-driven decisions to boost customer satisfaction and bring higher revenues by analyzing real-time data. Using big data, Fitbit tracks health data in real-time including sleep, eating, and activity habits to allow for better lifestyle choices. The data collected by Fitbit not only helps individuals to become healthier, but it also provides a clear picture of overall health and habits across a broader population to doctors and health care practitioners.

4. Build the Right Marketing Strategies:

With a pool of customer experience data including their preferences, dislikes, wants, desires, and more, you will create the right marketing campaigns around how, when and where the audience should be targeted. You may make better choices of all kinds, from which type of push notifications to send, and which technique to use to maximize engagement. You can use big data to analyze demographic data of the consumers, and Social behavior to adjust your marketing messages to match your current interests.

Conclusion:

Mobile apps are more common despite their user-friendliness and advanced results. App developers must, therefore, work hard to deliver an app that's appealing and exclusive. Big data provides a vast array of knowledge on the actions of people, such as their interests, needs, location, etc. Nonetheless, it is important to appoint a team of experienced mobile app developers to make effective use of the data obtained from big data analytics.