Benefits And Potential Pitfalls Of Predictive Analytics

Define data analytics in general and provide a brief overview of the evolution of utilizing data analytics in business

Decision making and communication are at the center of business success and efficient business analytics would only be effective through the use of proper information systems and that are up to date with current trends as well as optimizing on the available channels.

The theme of this book is how businesses in today’s world use ever-improving technology to collect data, convert it into information and business intelligence, and combine this information and intelligence with the knowledge of the workers to help make the best decisions they possibly can for the benefit of the company and the customers. Throughout the book, there are discussions on the different ways that technology can help a business with this process. When going into detail about the various information systems, this book also brings into

The concept of analytics-based decision marking takes into consideration industry knowledge and business analytics which includes four acts (Bartlett, 2013). The four acts help prepare analytics to support an anticipated decision and illustrate a process for analytics-based decision making. As a result, the role of statistical thinking, the interaction, and relationship between industry knowledge and analytics, as well as where things can go wrong in a real business problem can be revealed (Bartlett, 2013). In addition, moving from one act to another seamlessly, jumping back from and forth from one act to another or simply following some other route is easy to do in a real business problem. This annotated bibliography will examine articles that contain resources that support the concepts contained in the four acts.

Forecasting analytics will enable SYSCO to make appropriate upfront decisions and monitor customers as well as the industry. Extraction and data mining are also useful tools that will positively affect SYSCO’s decision-making process. Lastly, consulting support and employees’ training will facilitate the implementation of the new software in the company. For all these reasons, the use of BI at SYSCO can create a competitive advantage of the company in the industry. However, this competitive advantage depends on the competition – do the competitors use a similar software or by chance the same and do they already have a strong position in the market? Outperforming for example “U.S Food Service”, SYSCO’s main competitor, might be arduous if that company relies on a similar software and already has an eminent role in the

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die is a

Secondly, predictive analytics not only use statistical algorithms and forecasts on historical data but also anticipate likely situations to plan ahead. The means of these predictive models differs depending on their behaviour and future events but the aim is to go beyond reporting what has happened in providing the best assessment of what will happen. Data mining is an important component that tends to identify trends, patterns and relationship. They largely depend on statistical models and multivariate analysis techniques. Thereby decision making can be streamlined and new insights can be revealed leading to better decision making. Organisations are adapting to predictive analytics for competitive advantage. They are used in identifying trends, understanding customers, enhance business performance, predict behaviour and drive decision making. (SAS and Nyce)

There is a lot of hype recently around big data and its potential. When leveraged correctly big data can provide many great benefits for organizations in almost any industry. Some organizations currently have a lot of big data they have gathered throughout their life but have no current way of leveraging this data. One of the ways companies are able to leverage all of their big data is through predictive analytics.

All in all, the notion of predictive analytics in a more advanced manner would probable change the way e-platforms work. Few of the currently implemented predictive analytics examples.

This group project gives a report on data analytics. It consists of definitions of data analytics. It also defines Business Intelligence and explains the difference between Business Intelligence and data analytics. It also examines benefits, challenges and the implementation challenges of data analytics. In addition this project Analyze the means of Data Analytics to provide a competitive advantage to businesses.

Upper management is under pressure from shareholders and stakeholders alike to use more data analysis in order to drive all parts of the business. “As data use grows in sophistication and reliability, it is shaping a brave new world of data analytics that is starting to redefine how companies make decisions and drive improvements to their essential operations (Richardson, 2016).” Recent competition has caused sales to stagnate and the first quarterly miss on revenue vs. expectations in the company’s history. Management believes the newly created analysis team can create efficiencies that employees may not see in the course of their day to day operations. Specifically, for the sales team, the analytics team believes they can give sales

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 &

The proliferation, ubiquity and increasing power of computer technology has increased the volume of data oday`s mobile technologies and social media have collection and it`s storage manifold. This led to unleashed an exponential increase in information. continual growth in the size of data sets with Predictive analytics, a business intelligence technology consequent increase in complexity as well. Hands-on is one of the latest to take the future by storm with its data analysis is being increasingly augmented with immense potential for data- mining and efficacy. indirect, automated data processing Predictive analytics can be defined as any solution that techniquesclustered together and known as DATAIJERTsupports the identification of meaningful patterns and MINING.

Making decisions is an important part of the business world. However, without the proper information and data, it is easy for decisions to be made poorly. For this reason, business intelligence has been simplifying the process of delivering information and data to key decision-makers ever since it was first developed.

The company deals in fast moving consumer products and requires an analytics system that helps it serve the needs of its stakeholders more effectively. It has three major rivals in the industry and seeks to streamline its supply chain and inbound inventory processes to improve its cash flows. This implies that the ability of its employees to gather and act on different sources of data will allow them a chance to perform their responsibilities in a timely fashion. Thus, by becoming more conversant with various trends in the market, the organization will be in a position to predict future performance in its key business units. Moreover, modern firms