Big Data And Sustainability : Business

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

There is at least one field that is largely underutilizing big data and big analytics. This field is small business. Small businesses provide more than half of the jobs in the U.S. (Baldwin, 2015, para. 1), and yet, many of these businesses do not take advantage of the information that big data and big analytics can provide them. There are many ways big data and analytics can increase profits for small businesses, as long as these small businesses identify the opportunities that allow big data to work for them and as long as they work through the challenges that discourage small businesses from utilizing big data and analytics. This paper will discuss these opportunities and challenges in detail.

The promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.

Data collected by a business includes internal data, such as financial or operational information, as well as external data, such as customer or website usage information. Properly analyzing and acting on this vast amount of data can transform the way companies do business and can become their biggest competitive advantage. Leaders of the organization no longer have to rely on their “gut instincts” to make key decisions, instead they will make decisions off historic data and will be able to more easily measure and track the effectiveness of those decisions.

Today, data is a growing asset that various businesses are having difficulty converting into a powerful strategic tool. Companies need help turning this data into valuable insight, which can diminish risk and enhance returns on investments. Companies are struggling to make sense and obtain value from their big data. Superior and reliable

Over the past several years, the term “Big Data” has been used more frequently to help

We are now, more than ever, aware of the potentially negative impact of business on the environment, whatever the nature or size of the business. There can only be positive results from developing sustainability-from benefiting your own bottom line to benefiting tomorrow 's industry to benefiting the environment in which we all live (Crowther, D., & Aras G.,2008).

Every organization, be it a booming corporation, a start up non-profit, or even a national football league team, is comprised of a plethora of data. Although data has always been important to an organization, now more than ever it has become a critical part of their performance. With continuously advancing technology becoming available for companies to use, the amount of data accessible can seem almost endless. Figuring out how to manage this data, along with what to do with it can be a daunting challenge. This is where data analytics comes in. By simple definition, data analytics is the science of using the raw data collected to come to conclusions to make, hopefully, successful business decisions. There are many different facets of data analytics, and each facet can be uniquely important to an organization’s needs. Most data collected can be divided into one of three subgroups that each build upon the previous: descriptive, predictive, and prescriptive.

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

Big Data has gained massive importance in IT and Business today. A report recently published state that use of big data by a retailer could increase its operating margin by more than 60 percent and it also states that US health care sector could make more than $300 billion profit with the use of big data. There are many other sectors that could profit largely by proper analysis and usage of big data.

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 &

A Big Opportunity: Big Data. Big Data is simple – they are big chunks of information that needed special databases for them to receive, store, share and analyze information. Big Data is often used by the government, including procurement since it allows a lot of information to be fed into the database. In terms of public procurement, big data can help and improve the process in terms of spend analysis and supplier information. For businesses, big data can be a growing trend since a lot of information is processed by both the business and the consumer. The business can collect data from the client’s user experience using many avenues

Data is the backbone of business today and has always played a critical role in business. Today in the era of “Big Data” and Digital Business, data has become the primary driver of decision making, growth and innovation. The big data today is radically different from the data of yesterday. The Big Data age has brought with it a tremendous increase in the amount of data and types of data available to businesses. New data is produced every day, generated by social networking sites, mobile phones, location, third party, business transactions, etc. We are in an era which is characterized by the 5 V’s of Big Data: Volume, Velocity, Variety, Veracity and Value. The Big Data opportunities are enormous, as are its challenges. In this context it is especially important to understand the Opportunities and Problems that business faces to extract value from Big Data Analytics.

If the Information Age began in the 1990s with the rise of digital technology, then we’ve now officially entered the Age of Big Data, wherein companies like Google, Facebook, IBM, Teradata, Oracle, and SAS have the capacity to gather a lifetime’s worth of data about customers and their behavior.

It is hard nowadays not to hear news about “big data”. As technology continues to grow, companies are constantly trying to leverage them to remain competitive. Scientists, governments, and even the media are now also invested in extracting big data for their uses. McKinsey Global Institute (2011) defines big data as “datasets whose size is beyond the ability of typical database software tools to capture, store, manage, and analyze”. Furthermore, Barnatt (2012) explains that big data can be categorized into the three V’s: volume, velocity, and variety. Technologies like the internet, smartphones, computers, appliances, and automobiles are creating expansive amounts of data every second which contributes to the volume of data.