The Evolution Of The Data Stored Essay

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.

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.

In 2012, it was estimated, that human beings were generating around 2.5 exabytes of data every day and that number is likely even greater today (McAfee & Brynjolfsson, 2012). Twitter processes on average about 5,700 tweets per second (Twitter Inc, 2013). All of this data is stored in numerous ranging traditional database tables and spreadsheets to SMS text messages, PDF files, HTML web pages and more. While the value in capturing and analyzing this data is clear, the solution is not. Traditional data warehouse technologies were not designed for this volume, velocity and variety of data, which is collectively referred to as big data.

Additionally, social networking website Facebook, stores approximately 40 billion photos in total. (“Data, data everywhere”, 2010) Besides enormous data that generated from daily operational company transactions and social networks, the price drop of the data storage is also a strong factor triggering the fever of “Big Data”. For example, Google Drive - a cloud based data storage service – had a price drop of approximately 80% from March 2014. This price drop is considered a marketing approach to attract more computer users to adopt Google’s cloud service, which provides a more convenient and efficient way to access and store daily-used files. Although emerge of enormous data provides us opportunities to conduct further investigation and benchmarking, valuable information are not fully extracted and the potential power of using “Big Data” is undermined. In order to achieve thoroughly extraction of useful information from databases, many professionals in the academic field devoted into the study of data analysis and identified two of the most important drawbacks of traditional data analysis, which lacks of predictability and is less flexible in scalability.

Today ‘Big data’ is more popular than before, the performance of a database is becoming extremely important, including family life, school studying, office work and all business. Providing reliable and faster database services is the goal of organizations including any business, schools, and

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.

Data storage and management technologies have recently begun to surge in popularity. Businesses want to learn how to implement the best ways to store, maintain, capitalize on the copious amounts of data that their products, consumers, services, etc. generate. With that being said, organizing and measuring data has proven to be quite difficult despite present-day technological innovations. The term “Big data” has emerged and Apache Hadoop, or Hadoop, technology uses a set of algorithms to process large clusters of data (Kelly, 2014).

Abstract— The Data which is structured and unstructured and is so large with massive volume that it is not possible by traditional database system to process this data is termed as Big Data. The governance, organization and administration of the big data is known as Big Data Management. For reporting and analysis purposes we use data warehouse techniques to process data. These are the central repositories from disparate data sources. Now Big Data Management also requires the data warehousing techniques for future predictions and reporting. So in this paper we touched certain issues of data warehousing usage in Big Data management, its applications as well as limitations also and tried to give the ways data warehousing is useful in Big Data Management.

Big data is not a hype, but it is the future. The big data industry continues to advance, and big data service providers are making it easier for companies to work with big data in driving their businesses. Progressively, greater volumes and varieties of data will be incorporated with more business processes to support better decision making and greater insight. Moreover,

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.

Data is a powerful weapon as well as a resource. Having data does not make you powerful but what you do with it makes all the difference. Companies like Amazon, eBay and Netflix are already using data to predict user behavior and utilizing that to increase their revenue. But processing data in real time is not an easy task. The data today has great volume, is veracious in nature and is increasing at an enormous rate and hence has been given the term Big Data. There is a constant research going on to find a solution to process such huge amount of data in real time.

Data are a vital organizational resource that needs to be managed like other important business assets. Today’s business enterprises cannot survive or succeed without quality data about their internal operations and external environment. This growth drives corporations to analyze every bit of information that is extracted from huge data warehouses for competitive advantage. This has turned the data storage and management function into a key strategic role of information age.

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

Thought behind the motivation of the author is throw insight on Big Data its emergence, necessity, essence etc. In this paper the fact that everyone are a part of big data is been mentioned, web is the main source of data. Big data is defined as quintillion bytes of data His exact words are given as “Big Data is the fuel. It is like oil. If you leave it in the ground, it doesn’t have a lot of value. But when we find ways to ingest, curate, and analyze the data in new and different ways, such as in Watson, Big Data becomes very interesting.”Tools that are used to nalyse the big data such as Google BigTable ,Hadoop and MapReduce that revolutionized the organizations has been discussed. Parallel and distributing computing model and the importance of 7 V’s (volume, velocity, veracity, validity, variety, volatility, variety) in finding the true value of Big data has been discussed

In today’s world, the amount of unstructured data collected is humungous. This unstructured data is of no use if it is not properly processed, analyzed and evaluated. Using this data for the betterment of mankind is what most of the largest companies like Google, Facebook, Amazon, Netflix and much more are targeting. Big data is a term for datasets which are so large and complex that traditional database systems such as MS SQL, MySQL, etc., are incapable of handling them. It is not the amount of data that is important, but what organizations do with data that matters the most. Data can be mapped to useful information which can be further utilized for analyzing and drawing insights that lead to better management practices and strategic