Big Dat An Essential Part Of Every Business Operation

Big data analytics is the process of analyzing large data to find useful information such as improving efficiency of business, market trends, customer’s preferences, information of competitors, and other useful business information. According to the IT Glossary, “Big Data is high-volume, high-velocity, and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.” In other words, it is an abundant array of information used to acquire insights and make business decisions.

The data analytic process is one in which a large amount of information is collected using software specifically geared towards collecting, identifying and storing information for use by the company. The information is gleaned from different forums, with social media being the most rich and useful. The information is then quickly sorted and organized for use by the collecting agency (Turban, Volonino, Wood, & Sipior, 2002, p. 6). The use of data analytics really took flight in 2010 when different companies offered software that enabled a company to implement their own data analytics. This led to better marketing campaigns, improved customer relations and it gave companies using the software a bigger advantage over their competitors (Savitz, 2012).

Since the 1970’s databases and report generators have been used to aid business decisions. In the 1990’s technology in this area improved. Now technology such as Hadoop has gone another step with the ability to store and process the data within the same system which sparked new buzz about “big data”. Big Data is roughly the collection of large amounts of data – sourced internally or externally - applied as a tool – stored, managed, and analyzed - for an organization to set or meet certain goals.

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

New organizations can leverage Big Data in such a way that it provides benefits that can prove valuable especially to an organization seeking to establish itself and grow. One of these benefits is faster and better decision making. Particularly with the analytics of Big Data, organizations have access to real-time data

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.

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 the present most-liked theme of today 's technology. These research goes through all description of techniques and technologies of extracting of the data, storing of data, distribution of data, analyzing of data, managing of data with high velocity and from the structured data and helps in the handling of the extreme data. Big data has the presentation the capacity to improve predictions, saving money and enhancing the decision making process in the fields of the traffic control, weather forecasting, disaster prevention, fraud control, business transaction, education system, health and the national security.

Big data is buzzword in every field of business as well as research. Organizations have found its application across various sectors from Sports to Security, from Healthcare to e-Commerce.

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

Data is being produced at a huge rate and 90% of the data which exists today were produced in the last two years. Thus, it is difficult to manage big data which are extremely large, structured/ unstructured data sets analyzed to find trends, associations, reports, etc. The biggest challenge today is to find the quickest and the most inexpensive tool to analyze the big data which consists of emails, videos, pdf, audio files, and tweets. Predicting future with being able to access and store real time data is the future of BI and big data analytics (Jamack, 2012). When BI reports are run using the data and queries, information is retrieved and it is called Descriptive Analytics. When the dataset is further analyzed and drawn inferences using statistical methods like correlation or regression then it is called Diagnostic Analysis. Based on this information when the possible outcomes are predicted it is called Predictive Analytics. Finally, Predictive analytics uses previously tested or predicted models which are put into a reiterated process to produce an anticipated outcome. Big data technology combines all of these analytics, along with being fast and efficient in handling real time data (Payandeh, 2013). Business Intelligence consists of different tools to make better informed decisions with the data they have. Traditional BI were focused on the OO of the OODA loop (Observe, Orient, Decide, Act) but the modern BI needs to directly integrate the Decide and Act since there is a

The term “Big Data” has been around for quite some time and has been catching everyone’s attention with remarkable speed. A plethora of questions do pop up in our mind sometimes. What is big data, is this something absolutely new, how can it be leveraged to create value for an organization and so on. For many years, companies have used various transactional records stored in relational databases to make competitive business decisions. But how long can we sustain or depend on these traditional methods of doing analysis and coming to a conclusion. There is an ocean of non-traditional, less structured data such as weblogs, social media, email, sensors, and photographs that can be mined not only for useful information but also to make strategic 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

Big data is an extensive collection of structured and unstructured data. It is a modern day technology which is applied to store, manage and analyze data that are not possible to manage, store and analyze by using the commonly used software or tools. Since all of our daily tasks are overtaken by the modern technologies and all the businesses and organizations are using internet system to operate, the production of data has increased significantly in past

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.