The History Of Big 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.

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.

Big Data is garnering great recognition for its data-driven decision making methodology. Right from data acquisition where there is a flood of data available, we need to make effective decisions about usage of data. Privacy, scalability, complexity and timeliness are the problems that hinder the progress of Big Data.

According to the article, 2.8ZB of data has been created and replicated in 2012. The proliferation of devices such as PCs and smartphones worldwide, increased Internet access within emerging markets and the boost in data from machines such as surveillance cameras or smart meters has contributed to the doubling of the digital universe. IDC projects that the digital universe will reach 40 ZB by 2020, an amount that exceeds previous forecasts by 14%. Thus, data is not narrowed to big only; it is actually huge. Like, 40 ZB data is the equivalent of 1.7 MBs of new information created by the every single human for every second of the day. Developing countries like China and India are currently covering 36% of digital universe; the prediction says it will be increased up to 62% by 2020. So the companies will have numerous scopes to dig out more data and analyze them as per their requirement. Despite the unprecedented expansion of the digital universe due to the massive amounts of data being generated daily by people and machines, IDC estimates that only 0.5% of the world’s data is being analyzed.

Not only the development of Big Data brings big opportunities, but it also brings big

It is that time of year again, to sit back, and reflect on everything that has happened in the past year and to make predictions of what will happen in the years to come. The new job that is starting to move out of the woodworks is ‘Big Data.’ These large volumes of data are being used in ways no one could have imagined years ago. Data analysts are using this newly found information to improve the world around us, from helping companies make a more efficient profit, research the climate changes, or improve how people live their daily lives.

The ever-increasing advancements in technology, and the way in which we are aiding in the creation of more and more data every day, there’s an idealism that we analyse this information to provide meaningful results, whether it be in our jobs or to support our businesses. The benefits of using and supporting big data will lead to a greater competitive advantage and “will become the basis of competition and growth for individual firms, enhancing productivity and creating significant value for the world economy by reducing waste and increasing the quality of products and services” (McGuire, Manyika and Chui, 2012), now and in the future. However, there is also some issues that may arise that businesses will need to address, particularly in privacy and security, in which risk management strategies will need to be implemented.

In today’s world, data is being amassed at an unprecedented scale. Large amounts of data generated by and about people and their interactions are being collected, analyzed, and stored for future use. Organizations are able to gain access to a variety of data sources including call logs, text messages, emails, client chats, social media pictures, videos, and posts, RFID, Geographic Information Systems (GIS), and much more. The reception of Big Data is described by boyd and Crawford (2012) as being “seen as a powerful tool to address various societal ills, offering the potential of new insights into areas as diverse as cancer research, terrorism, and climate change” as well as being “seen as

In 2012, the concept of ‘Big Data’ became widely debated issue as we now live in the information and Internet based era where everyday up to 2.5 Exabyte (=1 billion GB) of data were created, and the number is doubling every 40 months (Brynjolfsson & McAfee, 2012). According to a recent research from IBM (2012), 90 percent of the data in the world has been created in the last two years alone, and Internet activity in each second today will generate more data than all the data combined in the

Understanding what big data means is really simple.” It is being generated by everything around us at all times. Every digital process and social media exchange produces it. Systems, sensors and mobile devices transmit it” (Big Data Analytics).Big data is being produced by everyone and every day that finding ways way to manage this data is becoming a challenge. It arrives from multiple sources or touch points such as websites, social media or apps on smart phones at a high velocity, volume and variety. “All kinds of technologies or approaches including mobile devices, remote sensing technologies, software logs, wireless sensor networks, social media etc. are used by organizations to collect big data. (issue, 2013)” Now that the meaning of ‘big data’ is clear, it’s important to know that this information is useless unless it’s processed properly with the right tools. To extract meaningful value from big data companies spends fortune; it requires optimal processing power, analytics capabilities and skills.

The term big data came into the picture to refer the big volumes of information’s both the companies and governments are storing. The data may be where we live, where we go, what we buy and what we say etc. all will be recorded and stored forever. More than 90% of data is generated in the past 2 years only and this volume is increasing day by day and doubling for every two years. In this world, the organizations are using the data generated by us and no one knows what they are doing with the collected data. Big data is defined as a lot of structured and unstructured data from different sources, such as E-commerce websites, online transactions, social networks, medical records, internet search indexes, banking and financial services, scientific searches, weblogs, and document searches and so on. Big data also can be described by four V’s: Volume, Velocity, Variety and finally Value.

TITLE A Big Data is fast becoming a ubiquitous term in the world of computers – but what does it actually mean? Explain the fundamental principles of Big Data and discuss the impact it is having, and may continue to have, on modern computing. What challenges does the model bring and in what ways can these be resolved?

Data has always been analyzed within companies and used to help benefit the future of businesses. However, the evolution of how the data stored, combined, analyzed and used to predict the pattern and tendencies of consumers has evolved as technology has seen numerous advancements throughout the past century. In the 1900s databases began as “computer hard disks” and in 1965, after many other discoveries including voice recognition, “the US Government plans the world’s first data center to store 742 million tax returns and 175 million sets of fingerprints on magnetic tape.” The evolution of data and how it evolved into forming large databases continues in 1991 when the internet began to pop up and “digital storage became more cost effective than paper. And with the constant increase of the data supplied digitally, Hadoop was created in 2005 and from that point forward there was “14.7 Exabytes of new information are produced this year" and this number is rapidly increasing with a lot of mobile devices the people in our society have today (Marr). The evolution of the internet and then the expansion of the number of mobile devices society has access to today led data to evolve and companies now need large central Database management systems in order to run an efficient and a successful business.

Now-a-days the Data usage has increased a lot. Data that the human race has accumulated in the past one decade, far exceeds the data that are available to mankind during the preceding century. They also expect that different stakeholders such as consumers, companies and businesses are likely to exploit the potential of Big Data. Several estimates about the accumulation of data have challenged our earlier imagination. Data scientists are increasingly using data quantities in Peta and Zeta bytes. There is no doubt now that