The New Frontier : Data Analytics

Just like in baseball there are large and small businesses. Businesses have to make decisions, decisions that will help the business in the long run. By using analytics business can measure their performance to know where they stand financially and economically. Numbers are very important in a

2. Analyze the main advantages and disadvantages of using data analytics within the industry or company that you have chosen.

Data analysis is a procedure of inspecting, cleaning, transforming, and modelling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. There are multiple facts and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains in data analysis. For data analysis we have to mine the data first for our purpose such that the data we can handle easily. Basically for data analysis our first thing to do our planning, how we are going to collect the data, our going data going to make sense or not, actually data will be meaningful for our object, after

In today’s companies, the analytics software plays the important role and guides the future activities to a great extent.

Each type of analytics as seen on the diagram above, could share a common sub group which could in turn have additional classifications. understanding and reviewing the different types of analytics systems and choosing those that best suite an organization is very helpful in determining the analytic plan for the future of the business. Succeeding in this, will definitely give a boost to the overall value of a business platform.

Stage 4, Analytical Companies – Analytics have been applied at an enterprise-wide level and are being used to drive decision-making, performance, and innovation, but results may not yet have been realized

Businesses today have access to significantly more data than any other time in history; however, most businesses are not capturing or using the data effectively. A report by the Aberdeen Group, “The Executive’s Guide to Effective Analytics,” indicates that “44 percent of executives are dissatisfied with the analytic capabilities available to them today, and that they often make critical decisions based on inaccurate or inadequate data” (Forbes, 2014). Luckily, CEO’s are beginning to recognize the need for analytics and more and more businesses are making a shift towards a data-driven business culture.

In the New Science of Winning book, (Davenport & Harris, 2007, p.7) 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.” [1]. To be successful in today’s competition, my current employer, DLL Financial Solutions Partner (DLL), is competing on analytics and fully aligned its core strategies to be supported by extensive statistical and computer based decisions. DLL is a global financial services company with operation in 36 countries, and its main focus is in the commercial equipment finance sector. In the following paragraph, I will explain DLL’s position in the industry and its ability to successfully compete on analytics with regards to its core business functions.

Today, the world’s trend in operating business focuses on data availability to enact the best suitable decision to improve, develop, and increase business revenues. Moreover, the availability of data helps to monitor and control the quality of provided products or services. However, the availability of data without proper analytics operations would have no meaning (1). Data analytics provide an important aid to an organization to figure out their position in the market in comparison with their competitors. Also, data analytics helps to identify what is the organization’s competitive ability in the market, what they should bet on, and what they should strive for. With that being said, many of today’s most successful organizations utilize

Business analytics on the other hand, as defined on Wikipedia (2012, Aug 06) "refers to the skills, technologies, applications and practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning." It goes on to state that, "Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods." This is in contrast to business intelligence and stated above. Business intelligence answers questions such as what happened, , how often, how many, where the problem is, and what needs to happen next. Business analytics answers questions like why is this happening, what if these trends continue, what might

Analytics is one of few ways to gain insights to meet your customers’ needs. It helps bridge the gap between providing a service to solving real problems.

Out of all the profiles or positions out there in information technology I aspire to work as a data analyst which in some cases is also referred to as a data scientist. This is because I am good with numbers and statistics and fascinated by data. With the combination of my courses taken in my Master’s degree and my past industry experience, I am looking forward to work in the field of data science and data analytics. I would like to use my technical skills to draw out business information and help the organization understand the impact of the trends and numbers on the business and thus, help them improve their existing processes. Analysis of data is a process of inspecting, cleaning, transforming and modelling data with the intent of discovering useful information, predicting

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

Business analytics is different to Business intelligence which also uses statistical methods. Business analytics uses statistical methods and data to arrive at fresh understanding and illumination of a situation, whereas business intelligence uses statical data to serve as querying, reporting or alerts. Business analytics, therefore, is, one may say, the detective side of business using the statistics to develop and progress the business or direct it in new directions rather than revamping it with existent and supportive data. Business intelligence, in other words, uses the data to inform stakeholders and others what is occurring with the business, what the action is, and what steps are being taken.

Broadly, there are two types of Analytics i.e. Business/Cube Analytics and Predictive Analytics. Business Analytics is a traditional way where historical measures (revenue, profit, loss etc.) available are extracted, transformed, modeled and stored for analysis. It is about getting insights on events that already happened. E.g. Year-on-Year sales report. In the contrary, Predictive analysis applies data mining and statistics on large volume of data for Forecasting, projecting, and predicting. E.g. KFC giving combo offer based on prediction of consumer’s possible purchase behavior to increase overall sales.