Big Data, Analytics And Modeling

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.

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 Analytics is the process of analyzing large amounts of raw information generated and stored. In today 's fast paced technologies, we are inundated with in a tsunami of data before us. All applications, in a broader range are depending on data in a remarkable way. BDA is driving almost every field in our society from Retail, Manufacturing and Mobile applications to life and physical sciences. The Data Analytics techniques are performed to uncover hidden patterns, unknown correlations and other useful information. Earlier, Data Analytics were based on guessing and inaccurate data models but currently this can be done directly. Big Data has truly revolutionized scientific research (Computing Research Association 2014).

Big Data can analyze a customer’s purchases, profile information, and make an accurate prediction on what his/her interests will be. Big Data has the potential to be the phenomenal tool of the future. It can accurately predict what a customer wants and show advertisements that he or she is actually interested in; It can be installed in smart cars, where an automatic distress call is sent when an unlucky individual is in a car accident; It can be uploaded to devices that closely monitor people’s health and report any irregularities to their doctor.4

The amount of data in our world has been rapidly increasing and analyzing these large data sets, or big data, has become crucial for businesses in increasing their success. Many businesses use big data to model their business structures, control processes, and run the business. The availability of this data leads to a more accurate analysis of the target market. More accurate analyses lead to more confident decision making and better decisions means greater operational efficiencies, cost reductions and reduced risk. There are many ways in which big data can be successfully implemented in an organization. Big data allows businesses to segment their target market, creating more precisely tailored products and services. Big data is also used to conduct controlled experiments to make better management decisions. Finally, big data can unlock value by making the captured information transparent and usable at much higher frequency (Manyika, “Big data: The next frontier for innovation, competition, and productivity”).

Big Data is becoming more meaningful with the ever more powerful data technologies, which enable us to derive insights from the data and help us make decisions. Big Data also creates new courses and professional fields such as the data science and data scientist, which are aimed at analyzing the ever growing volume of data. Some might think this exaggerated because data analysis, after all, not a new invention. However, we might all agree that the progress of digitization associated with the generation of ever larger amounts of data have totally changed the ways we deal with data.

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.

Data is the most valuable tool in your business. Based on a Gartner survey, 73% of organizations have invested or plan to invest in big data within the next two years.

Firstly, the main problem is deciding which data should be selected. The data, explaining customers’ desires and needs, is important to be collected while most of the enterprises are confusing about 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 did not 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 data complexity.

In this modern age of constant technological advancement and business innovation, a relatively new feature has unlocked more potential for businesses to improve: Big Data. Big Data can be defined in many different ways. It has become important primarily for business decision making.

A look at almost any of the marketing magazines from the last six months will uncover a large number of articles on “big data”. Examine the subject and discuss how it is relevant to companies like Tesco.

Managing and analyzing big data is a huge task for all organizations of all sizes and across all industries. If a business’s plan to implement a data management tools there is a need for a more realistic way of capturing information about their customers, products, and services. Mining data is often in the terabytes and organizations need to be able to quickly analyze that data and then pull appropriate information needed to make managerial decisions. Further, with the insurgence of social media, smart devices and click-stream, data is generated daily on global networks through interactions. The use of data management technologies allow a company to interface unstructured data and structured data to gleam information that is usable for business managers to make sound business decisions, improve sales and to decrease operating costs. Big data integration and analysis has evolved for organizations to store, manage, and manipulate vast amounts of data then provide the appropriate information when it’s needed to meet business objectives.

Big data is not a hype, but it is the future. The big data industry continues to advance, and big data service providers are making it easier for companies to work with big data in driving their businesses. Progressively, greater volumes and varieties of data will be incorporated with more business processes to support better decision making and greater insight. Moreover,

To stay competitive in today’s market, “companies are using big data analytics to understand and engage customers in a way that inspires greater loyalty” (Rackey, 2015). Better understanding our customers will result in opportunities for increased sales through up-selling and cross-selling while also improving customer satisfaction by catering to customer’s needs more efficiently. Developing a BI program using data, technology, analytics, and human knowledge allows us to transform data into useful BI solutions.