The Current Ways Of Storing And Reading Mass Data

Every day, we produce 2.5 quintillion bytes of data. 90% of all data in the world was produced in the past two years. Data has been around forever; we have always gathered information. Paleolithic cavemen recorded their activities by carving them in stone or notching them in sticks. Egyptians used hieroglyphics to record significant events in history. The Library of Alexandria was home to half-a-million scrolls of the ancient world. Less than hundred years ago, we used punch cards to record and store information. As technology continues to evolve, the amount of data we store continues to grow. We’ve come a long way since stone tablets, scrolls, and punch cards. It’s important to understand the concept of big data and the impact is has created. This paper will define the classifications of data, explain the challenges of big data, and describe how big data analytics is being used in today’s data driven world.

Big data and its definition has changed over the years. In a 2011 research project by MGI and Mckinsey’s Business’ defined big data as

Business thrive when they have the most accurate, up-to-date, and relevant information at their disposal. This information can be used for a plethora of pertinent markers in small and large businesses, relating to accounting, investments, consumer activity, and much more. Big data is a term used to describe the extremely large amounts of data that floods a business every day. For decades, big data has been a growing field, facing controversy on many levels, but as of late, it has been a major innovator in the challenge of making businesses more sustainable. Big data is often scrutinized for its over-generalization and inability to display meaningful results at times. When applied correctly, data analysis can bring earth-altering information to the table.

Big data is buzzword in every field of business as well as research. Organizations have found its application across various sectors from Sports to Security, from Healthcare to e-Commerce.

As a result of the appearance of big data in our world, conventional data warehousing and data analysis methods no longer have the process power needed. What is Big Data you may ask and why is it such a big deal. NIST defines big data as anywhere “[…] data volume, acquisition velocity, or data representation limits the ability to perform effective analysis using traditional relational approaches […]” (Mell & Cooper, n.d.).

Big data is not as new as many people believe it to be. It is actually a concept that has been around for almost a century. It is just the “same old data marketers have always used, and it’s not all that big, and it’s something we should be embracing, not fearing” (Arthur). In 1944, Fremont Rider “predicted that the amount of data in the world would increase exponentially” (Hopp). Rider was right on target with his prediction seventy years ago. Data has grown much greater than he probably could have ever imagined back then.

Big data refers to the large amount of data that is impossible to handle by using traditional or conventional methods such as relational databases or it is a technique that is required to handle the large amount of data that is generated with advancements in technology and increase in population. Big data helps to store, retrieve and modify these large data sets. For example, with the advent of smart technology there is rapid increase in use of mobile phones due to which large amount of data is generated every second, so it is impossible to handle by using traditional methods hence to overcome this problem big data concepts were introduced.

The emergence of new technologies, applications and network systems makes it hard to run the current business models and huge data types, and thus emerged various types of analytic tools like Big Data, which make this work easier by way of proper organization of data. Big Data is all about analyzing different forms of data (Structured, Semi-structured and Un-structured) and it is not about the procedure, creation or consumption of data.

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

This increased the demand for data scientists across Europe. The larger the volumes of data the greater the complexity of data and analyzing of data. Getting high varieties and volumes of data at greater velocities is the advantage of using Big data.(H. Davenport, 2014). The trend of making information from data has started from decision support followed by execution support, analytical processing, business Intelligence (BI) ended with Big Data. The design Big data architecture and

In a dynamic global economy, companies and organizations have started to rely more and more on statistics gathered from their customers insights and behavior, internal processes and business operations with the aim of finding new opportunities for growth. In order to find and determine this information, large complex sets of data should be generated and analyzed by skilled professionals. The compilation of this large collection of data is known as “Big Data”.

Big Data embraces structured, semi-structured and unstructured information. It can be demographic or psychographic information about the customers, their opinions, product reviews etc gathered from variety of sources such as tweets, blogs, other social media content, technical devices like sensors and stream of data from mobile devices. Businesses have started using Big Data to get right information to identify right markets and right customers at the right time in order to make right strategic decisions. The Big Data market is estimated to grow to $32.1 bn by 2015 and $54.1 bn by 2017. According to the report “Be Careful or Big Data Could Bury Your Bank”, the world creates 2.5 quintillion bytes of data daily and last 2 years have contributed to almost 90% of the data which exists today. It empowers institutions to learn more, create more and do more using the data available with them.

Firstly, the main problem is deciding which data should be selected. The data, explaining customers’ desire and need, is important to be collected while most of the businesses are confusing what data they should concentrate on. A recent Gartner report (2014) stresses that 64% of firms raced to plan or launch a Big Data project, though they didn’t have enough professional knowledge yet. To understand what customers need through Big Data possibly turns into the core of companies’ target. The large data volumes and different varieties of data lead to complexity.

The term Big Data is to a large extent vague and amorphous. Information technology professionals look at Big Data as large data sets that require supercomputers to collate, process and analyse to draw meaningful conclusions. A phenomenon defined by the rapid acceleration in the expanding volume of high velocity, complex, and diverse types of data. The new character added in this definition is

Big Data has seen exponential growth in recent years due to the large volumes of social-networking data that is now being produced. While it may be easier for large enterprises to adopt the use of Big Data it is unclear if many small and medium sized enterprises are firstly aware of Big Data and its uses and secondly whether it will actually be beneficial to the business. The project will look at the use, or lack thereof, of Big Data in SMEs and provide a comparison when looking at larger enterprises.