“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” — Jim Barksdale
Big Data analysis is completely transforming the modes and approaches of the present business scenarios. The concept consists of four key attributes — better known as the four Vs of Big Data: volume, variety, velocity and value. The volume of data whether structured or unstructured would aid business growth on a routine basis too.
Big data analysis can lead to helpful insights that would in turn aid better strategic business decisions. With the ongoing market trends in the mobile app world, the concept of Big Data has risen beyond storing enormous information and has made previously used analytical methods redundant.
How big is Big Data?
Many organizations have diverted towards new trends accepting the newer technologies to aid faster decision-making amid a volatile business environment. The use of mobile apps has changed tremendously in recent years, and the development process has also generated data that is enormous and tough to be processed systematically. Big Data serves to solve the data management problems seamlessly
Big data is a vast concept and bigger in its impact; since it depends on how one goes about it.
The volume of data has increased enormously. There are a variety of sources from where organizations consume their data. The major issue was collection and storage of such big data. However, with new age technologies like Hadoop, Cloud Computing and Spark, the burden has reduced considerably.
Processing Big data – compiling and making sense of unstructured random data
Everything you do in the internet world is adding up to the stack of zillions of data. Whether you listen to your favorite music, read ebooks, browse data or make online transactions, every bit of data gets stored. It is hard to believe any activity that does not generate data.
Billions of users actively use social media, and the organizations deal with recording that data at every millisecond. Every conversation gets stored with varied security layers. This affects the cost and time complexities.
The velocity at which the data streams are at an exceptional speed, and one must deal it in a timely manner.
In order to deal with torrents of data in real time, various new concepts have arrived in the market like sensor, RFID tags. Technology now allows us to analyze the generated data without the need of storing it into databases.
Types of data and their value for organizations
The daily apps you use like business card scanner store variety of data in every format — structured, unstructured, numeric, documents, images, videos, financial transactions and statements, stock data.
In the past, our focus was only on the traditional database approaches – dealing with database tables or relational databases such as financial data. On the basis of research done, nearly 80% of world’s data is unstructured. Big Data technology helps us to analyze such varied data bring it together in one place.
For instance, Google Drive not only stores images, document, PDFs, videos, but it also processes these data, stores and manages them in every possible format. Latest technologies like Cloud Computing, Hadoop with the latest analysis methods in the software market help us to gain more insights and add values in the digital world.
Organizations, which adopt these technologies, differentiate their compiled data in terms of volume, velocity, and variety. Face recognition, text analytics, voice analytics, fingerprints, etc. are now easily recognizable. In this way, Big Data helps enhance the value of raw data, converting discrete sets of information in an intelligible form, aiding decision-makers to make the most of it.
Big Data and its applications
Data is an important asset to every organization. Every organization needs to strategize its data and plan how to use, collect and secure it effectively. One must keep updated with the latest technologies in the ever-changing ecosystem and know about concepts like Cloud Computing and more of such frameworks. One can use big data analytics for tracking data and processing it in applied sciences, agriculture, transportation, financial transactions, and the like.
Refining and analyzing data helps business processes and helps professionals derive business intelligence too. Secondly, an essential aspect is the data security. Every mobile app development company creates and maintains privacy policies related to data and its process.
We see many apps share their data with others, but they always follow certain norms and policies and make sure that no data breach arises in any form. Facebook shares its data (user information, searches, likes and promotions) with Google, but with transparency involved, data is put to further use. Big data strategies make sure assets are converted to tangible information to aid businesses related to diverse domains.