Finding Solutions To Information Overload In Social and Technical System Strategies

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

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.

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.

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.

Competing on analytics is currently one of the most essential qualities for companies looking to gain a larger market share in their given industry. This is due to the fact that the easiest way for corporations to differentiate themselves from their direct competitors is to maximize efficiency through cohesive processes and decision making. Analytics is defined as, “The extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact based management to drive decisions and actions.” (Davenport, 2007, p.7) So in order for companies to compete on analytics they need to be willing to invest in the proper technologies that are able to compile all of this information and data into output that can be used

Big data and analytics are hot growth areas, not only for IT organizations, but for businesses across all industries.

Big Data is an outgrowth of the proliferation of databases and massive data sets. The insights needed to more intelligently manage an organization can be found in the myriad of data sets that comprise a Big Data platform. The greatest challenge of Big Data is contextual intelligence supported by integration to legacy, 3rd party and homegrown application systems located throughout an enterprise (Jacobs, 2009). To get ot his level of proficiency in analyzing Big Data sets and databases, enterprises need Business Intelligence (BI) and analytics tools that can parse through terabytes quickly, finding patterns and analyzing massive amounts of data, then distilling it down to key

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 came about the scene during the first decade of the 21st century. Those online and startup firms to survive the dot com bubble burst were the very first to embrace the technology. Companies like Google and eBay were a couple of the first firms to implement big data. They never had legacy systems to integrate big data into because they began with big data. “Big data could stand alone, big data analytics could be the only focus of analytics, and big data technology architectures could be the only architecture” (Davenport, and Dyche, “Big Data in Big Companies”). Even though big data was implemented from the get-go with firms such as Google, LinkedIn, and eBay, etc., it began to slowly descend into other companies that saw what

Big data is a process in which transforming audits is conducted. Along with this, some major challenges are also adopted in order to maintain the standards as well as to give training in the required processes and systems. It is also said and impossible to further corroborate that around 75% of the world’s data has been initiated as well as created in the past two to three years. The actual and well organized proliferation of the entire data has changed our lives, and the way we act as consumers too. Therefore it is correct to mention that this era of big data helps in reshaping the operations of the businesses and it helps in giving them greater insights as compare to the early days. Therefore this is one of the

The variety, volume and velocity (Lohr, 2012) of data have evolved in the present contemporary times with various companies and business embracing the benefits and advantages leveraged out of Big Data and its plethora of real life applications. This concept have taken a huge leap ahead in time and have find some innovative and creative ways to collect, store and analyze data which his enormous these days. The realm of e business and its applications in this industry are conquered by the means of big data.

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.

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

International data Corporation (IdC) predicts that the market for big data technology and services will reach $16.9 billion by 2015 with 40% growth over the prediction horizon. Not only will this technology and services influence big data technology providers for related SQL database technologies, Hadoop or Mapreduce file systems, and related software and analytics software solutions, but it also will impact new server, storage, and networking infrastructure that is purposely designed to leverage and optimize the new analytical solutions. Major attributes of Big Data are:

The three Harvard Review Business articles all addressed the revolutionary change in information and how it can be used. The first article describes it as “big data” and calls it a management revolution that helps make better predictions and smarter decisions. Big data is different from the traditional analytics in three ways: volume, velocity, and variety. The volume of data available on the internet is increasing every single day. Companies have so much data they can utilize that most do not know what to do with all of the information. Velocity entails the speed of data today. Real time data allows competitors to compete at the highest level possible and provide customers with what they want faster than before. Variety refers to the fact that data comes