Why Do Small Businesses Use Big Data?

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

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.

Big data is a term that describes a large volume of data. This data comes in the form of structured and unstructured data. Structured data is information taken and sorted in rows and columns while unstructured data is pictures, tweets, videos, and location-based data. It is not surprising to see many businesses today utilizing data for financial gain. Businesses are harnessing data and using it to make investment decisions, marketing strategies, fraud reductions, and much more. These businesses and organizations can expect to become more profitable, effective, and efficient, but pushes the limits

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.

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” – Geoffrey Moore, author and consultant.

In economically uncertain times, many businesses and public sector organizations have come to appreciate that the key to better decisions, more effective customer or citizen engagement, sharper competitive edge, hyper efficient operations and compelling product and service development is data — and lots of it (Cameron McNaught,2010). Today the situation they face is not any shortage of that raw material. In a way that the wealth of unstructured online data alone has swollen the already torrential flow from transaction systems and demographic sources but how to turn that amorphous, vast, fast-flowing mass of “Big Data” into highly valuable insights, actions and outcomes.

Organizations use Big Data to have a bargaining power of customers by using buyer’s history to anticipate the needs of those buyers or products or to find a suitable replacement for the product on the website being used, to secure a purchase before the buyer changes their mind. Big data can also be used to increase margins through price discrimination. Big Data can provide you with insights into the raw material prices paid by your supplier. Organizations control new entrants by tying customers to their product and services making it expensive for them to switch suppliers. Big Data is also used to identify and eliminate inefficiencies. It does this by making data more transparent. Large organizations relentless use of data to drive efficiency makes it difficult for new entrants to match

Big Data has several benefits and advantages that give businesses a competitive advantage. One of the benefits of Big Data is reduced costs. Davenport elaborates on the price comparison and how there is a huge contrast between Big Data technologies such as Hadoop and traditional architectures like data warehouses. It is difficult to compare how both of them function but it is clear that the price comparison favours the Big Data technologies as there are considerable cost benefits . This is ideal for companies dealing with large amounts of data.

Big Data has taken the business world by storm. By 2020, it is expected that the amount of digital information in existence will have grown from 3.2 zettabytes in 2014 to 40 zettabytes. Companies are doing all they can to capture this digital information and turn it into actionable insights. Currently, the total amount of data being captured and stored by industry is doubling every 1.2 years. Therefore, companies must find increasingly efficient solutions to store and analyze this incredible amount of data.

Big Data gives one the ability to collect, manage and analyze large amounts of data, leading to changes in the way companies deal with customers, resulting in increased profits and a competitive edge over other companies. Big data is

Firstly, the main problem is deciding which data should be selected. The data, explaining customers’ desire and need, is important to be collected while most of the businesses are confusing what data they should concentrate on. A recent Gartner report (2014) stresses that 64% of firms raced to plan or launch a Big Data project, though they didn’t have enough professional knowledge yet. To understand what customers need through Big Data possibly turns into the core of companies’ target. The large data volumes and different varieties of data lead to complexity.

This article discusses firms that are at the leading edge of developing a big data analytics capability. Business firms and other types of organizations are feverishly exploring ways of taking advantage of the big data phenomenon. Big data is increasingly the cornerstone on which policy making is based. Firms that are currently enjoying the most success in this area are able to use big data not only to improve their existing businesses but to create new businesses as well. Putting a strategic emphasis on big data requires adding an analytics capability to the existing organization. This transformation process results in power shifting to analytics experts and in decisions being made in real time.

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

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