Research on Big Data

The research proposal can be developed from the topic of big data to match up the demands of enormous data flow in the dynamic world. Data visualization tools at significant cost can help up in analytics of big data and can form an innovative research proposal for analysis and extensive research. The real time data and the use of techniques of big data in this domain can form an excellent topic of research calling for formulating methodologies and strategies to tap the untapped potential of this field and to experiment more in the field of research.

Businesses today have access to significantly more data than any other time in history; however, most businesses are not capturing or using the data effectively. A report by the Aberdeen Group, “The Executive’s Guide to Effective Analytics,” indicates that “44 percent of executives are dissatisfied with the analytic capabilities available to them today, and that they often make critical decisions based on inaccurate or inadequate data” (Forbes, 2014). Luckily, CEO’s are beginning to recognize the need for analytics and more and more businesses are making a shift towards a data-driven business culture.

The emergence of big data has provided different avenues for organizations to use data to improve different aspects of their respective operations. Be it customer service, research and development, or market position, Big Data has the potential to be a significant driving force in all these areas. However, there’s still a significant gap between the ability of Big Data to produce insightful analytical information based on real-time data and the ability of organizations to capture and utilize this readily available tool. This is, in part, due to the fact that the systems and processes necessary to fully maximize the usefulness of Big Data is currently lacking in most organizations. This lack of a conducive habitat for Big Data is further magnified in new organizations without any knowledge of Big Data. For organizations that have that have little to no knowledge of Big Data, there must be a thorough assessment of the benefits of big data and how they could improve the organizations overall place in the market. There also needs to be steps taken towards the design of frameworks that will enable the organization to better capture and utilize Big Data.

Big Data became even bigger and really peaked in the year 2003. More data was collected in that year than in the rest of history before 2003. In 2012 it was estimated that 2.8 zettabytes worth of data would be created in that year alone.

In a fast paced, business ordinated technological world the overall welfare of a company is tied to the success or failure to make the tough decisions. On one instance a company’s CEO might be able to make the choices based on experience, advice, or simple gut instinct. However, this is not the only skill one needs. There is a great deal of information to be found in being able to see investments in data and analytics. These decisions are based off of big data. Big data is a catch-phrase, used to describe a massive volume of both structured and unstructured data that is too large to process using traditional database and software techniques. The volume of data is in most cases is too big, moves too fast or it exceed the processing capacity the company has. Despite these potential drawbacks, big data contains the potential to help companies by improving operations and making faster, more intelligent decisions. This can be broken into three key parts, knowledge, data, and information.

In your business, you have your own big data challenges. You have to turn heaps of data about various entities into actionable information. The reporting needs of institutions have evolved from simple single subject queries to data discovery and enterprise-wide analysis that tells a complete story across the institution. While the volume, variety and velocity of big data seem overwhelming, big data technology solutions hold great promise. The way I see it we can use this as one of the biggest asset for the company. We have the capacity to see patterns recounting in real time across complex systems. Huron is marshalling its resources to bring smarter computing to big data. With the Huron big data platform, we are enabling our clients to manage data in ways that were never thought possible before.

The big data analytics is not only limited to the information technology department this kind of belief makes most of the supply chain mangers to ignore the economic value of the data which have been collected. The main things that most of the supply chain mangers should know is that they should have a large access of data which only have the economic value. They also should protect that data they have so that the data cannot be viewed by their competitors since their competitors will know the economic value of the data they have collected. Another very important aspect that most of the suppliers should know about large data which they have collected is how to creatively use the data to make decisions which will make their work easier. This is because most of the mangers have access to these data but they do not use the data to help them in making major decisions.

Businesses using data is not a new concept; however, the role of data within industries has increased dramatically over the years to the point that it is essential for a business to understand how to handle data in order to continue operations. In today’s bustling digital age, professionals credit a certain type of data called “big data” with helping businesses gain insight on consumers. Big data is created whenever you travel to your favorite restaurant, make a particular move in a video game, swipe your card to purchase your favorite pair of Crocs, or tell your Facebook friends what you had for breakfast. It is data that is too large to be captured and processed by standard business

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 is a term for very large amounts of formal and informal information that can be analyzed to find trends and patterns. The information can be about anything, but it needs to be processed in a way that will give it value and relevance. It can come in multiple formats and from different sources such as large databases, electronic records, social media, mobile phones, apps, wearable devices such as pedometers, and others. Different data sets are combined and contrasted in different ways to give perspectives and insights about a topic. It can be used in a seemly endless number of ways and people are discovering new ways to use it all the time, some of them entertaining. The largest areas of use include those relating to consumer behavior and choices, business procedures, healthcare, science and research, and law enforcement. People are also discovering its use in their personal lives as well for things like buying a home, dating, fitness routines and travel.

The era that we live in, in the year 2015 is considered the “big data” era. Industries all over the world are analyzing data and determining marketing and business processes to attract consumers. Data analysis which started off on a much smaller scale today can be used in much broader aspects from coupons you receive in your email, to advertisements you see when you use applications on your smart phone data also can be used to determine the frequent of a customer to a particular store or website. These are both processes of data analytics being used and conveyed in a way to attract customers or satisfy consumer needs. Data analysis focuses on finding the specific data to answer your question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to gain optimal results. Data is not a new concept in any form, the technology of today’s world makes obtaining and analyzing data easier. The recent decades have seen a fundamental change in the model of data analysis. IMB Tech Trends Report (2011) identified business analytics as one of the four major technology trends in the 2010s. According to Chen (2012) Business intelligence began its practice in business and IT communities just a few decades ago in the 1990s. In the 2000s business analytics was introduced to represent the key analytical components in business intelligence. The business intelligence and data analytics previously adopted in an

Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. And big data may be as important to business – and society – as the Internet has become. Why? More data may lead to more accurate analyses. More accurate analyses may lead to more confident decision making. And better decisions can mean greater operational efficiencies.

Industry is thriving to capture the flood of data present today. Every sector has millions trillions of data which is increasing with extreme velocity to be handled. Social media has been fueling up data growth exponentially. Although human race has been generating data for thousands of years but recent decade has put forward a new

Data analytics has drastically changed how business operate on a day-by-day basis. It can make or break a business. It involves “exploring huge volumes of data to provide greater insight and intelligence, and doing so quickly.” (Efraim Turban. Linda Volonino. Gregory R. Wood., 2013) According to the Better Business Outcomes White Paper that was published by IBM, IBM observed that the planet was becoming more instrumented, interconnected, and intelligent about five years ago. Twenty thousand engagements later, though not it doesn’t say how many years later, IBM has gained critical knowledge of how big data analytics can improve conditions for organizations in nearly every industry. (Better business outcomes with IBM Big Data &

The proliferation of data, process and system integration technologies, combined with the rapid advances made in analytics, Big Data, customer management and supply chain applications are power catalysts of disruptive change in enterprise IT. Given the fact that many legacy, 3rd party and previously disparate, disconnected systems are for the first time being integrated together, the amount of data available for analysis and decision making has never been greater. Add to this the torrent of data being generated daily through an enterprise's sales cycles, social networks subscribed to, and customer interactions, and the amount of data available can becoming quickly overwhelming. All of these dynamics taken together form the area of analytics and enterprise software called Big Data. As tempting it is for the analytically-minded to dive into these terabytes and explore for insights and previously-unknown associations in the data, to get the most value from the investments in BigData, analytics, and enterprise applications, governance-based frameworks need to be defined that align these systems to specific strategic objectives (McKendrick, 2012). The advent of Hadoop, H-Base, MapReduce and other data analysis and aggregation platforms and applications only become relevant in the context of strategic goals and their accomplishment (Rogers, 2011). That is why more