Brown, B., Chiu, M., Manyika, J. (2011), Are you ready for the era of big data? Retrieved
Through informational interviews with seven industry experts and a thorough literature review, the team explored the concept of “big data” and generated key insights which will guide the Federation’s approach as the organization develops its members’ data analytics capacities. Additionally, the team identified a clear business case for implementing data analytics at CDCUs using strategies appropriate for the level of resources within each individual organization. The team also developed a set of survey questions for the client to use when gauging the level of interest and capacity within any individual CDCU.
Big Data is the act of compiling large sets of data based on a single individual or groups. Everyone encounters data in their daily life--you are experiencing it when you log onto a social media account, when you stream entertainment online, or even when you are online shopping. When you do any of these things you are leaving behind a digital trace that can be accessed by just about anyone. In “Six Provocations for Big Data,” danah boyd and Kate Crawford raise questions regarding the nature of Big Data. What is considered public information? What is the ethical way to go about retrieving data from online sources? Is Big Data more harmful or helpful? How often do you encounter Big Data, or data in general? What is the relationship between data
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.
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.
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.
Although we hear the term ‘big data’ frequently now, the true definition of big data does not seem to have a singular, agreed upon definition. Depending on who you ask, big data can mean many different things. What would seem to be the most intuitive definition of ‘big’ data is not necessarily the correct one. Though the size of the data is an important aspect, it is not always the defining factor. According to Dell EMC’s video, Big Ideas: How Big is Big Data, big data is “any attribute that challenges the constraints of system capability or business need.”1 Will Hakes, Co-Founder and CEO of Link Analytics, claims that big data cannot be defined in precise terms and is, effectively, a “rallying cry.”2 Hakes does, however, agree that any
“Why Big-Data Is a Big Deal”. Big-data is a logo used to describe a massive volume of both structured (is information already managed by the organization in relational databases ) and unstructured data (is information that is unorganized and does not fall into a pre-determined model) that is so large it is difficult to process using traditional database and software techniques. In most companies, the volume of data is too big or it moves too fast or it exceeds current processing capacity. Despite these problems, big-data has the potential to help companies improve operations and make faster, more intelligent decisions.
Tom Davenport, an author specializing in business intelligence, analytics and business process innovation, defines big data in his recently authored book “Big Data at Work: Dispelling the Myths, Uncovering the Opportunities” as “The broad range of new and massive data types that have appeared over the last decade or so.”
The world is changing with respect to the growth in big data and to the way in which it is used. Growth in big data brings with it many challenges, but it also presents new opportunities. Figure 1, helps understand some of the big data related activities that are taking place in the world with respect to volume of data that is being consumed by these activities over the next 5 years.
Presence of big data is a very common phenomenon now days, specially when talking about medium to large size corporation. Manyika et al., in their article (James Manyika, 2011) defined the term big data as “large pools of data that can be captured, communicated, aggregated, stored, and analyzed”. To clarify they suggested that big data refers to data, whose size makes it impossible to be processed by the typical software used for database management. Gartner (Gartner, 2012)defined big data in terms of its characteristics of high volume, high velocity and high variety. By volume, he referred to the size of the data, by velocity he referred to the speed at which the data is created and by variety he referred to the range of types of data.
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,
The purpose of this paper is to give an insight of Big Data, its background and future opportunities.
One piece of information may be insignificant, but billions of data points can illuminate. That’s the underlying promise of big data and analytics, which observers have been calling a revolutionary development for several years now. But it’s difficult to know where a revolution is headed while it’s still unfolding. New research from the McKinsey Global Institute