Introduction. Predictive Analytics Is Quantitative Analysis

The analytics software is the useful tool and great supporter for organization to reduce workload, increase the productivity and create competitive advantages. The analytics software helps organization knows exactly what customers want and their purchasing power, which will assist the company makes best decisions whether big or small every day. What is more, the analytics software works like an effective predictor, which will help organization look forward to the future scenario and make the best plan. Also the software is the key business enabler

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

The concept of Business analytics is a component of business intelligence, it has evolved in recent years and now in the for front center of business. With the growth of technology and the continuing improvement

Having data is not valuable but using data is. Analytic insights are changing the way corporates strategize and also redefining customer expectations. Analytics is the new differentiator between success and failure in the cut throat e-commerce and internet services based industry. The huge proportions of data generated from the increasing number of smart phones, the social networks and the ever more penetrating internet are automating customer centric marketing and other services. The idea is to predict what a customer may want to buy even before the customer realizes what they need. The techniques to achieve these results are broadly classified as Predictive Analytics.

Data analytics is the science of examining raw data with the purpose of drawing conclusions about certain information that is drawn from the data. By gathering data, it must be captured and reviewed then it can be turned into information. There are different types of analytics such as descriptive, diagnostic, predictive, and prescriptive. Descriptive analytics will describe, what happened during the process. Diagnostic analytics describes, why did it happen. Predictive analytics describes, what will happen. Prescriptive analytics describes, how can the process happen with a different approach. By applying these different types of analytics, it will answer several questions during the auditing process. Involving analytics to a process it requires

Everything is on the same architecture so it is possible for applications and analytics to be restructured excluding information processing latency, and sense-and-response solutions can process on huge quantities of real-time data for immediate answers without building pre-aggregates. Thus sap hana provides real time analytics.

The City of Boston uses SAP technology for data analytics in three different ways. First, the city implemented SAP Strategy Management to track high-level strategies and goals. With SAP BusinessObjects business intelligence solutions, the City of Boston connects day-to-day operations to their strategic goals. With SAP HANA, Boston finds the hidden stories in big data, to become a predictive and proactive government.

The sections below go into greater detail about how organizations can use analytics as a competitive weapon to introduce new goods and services and support existing ones.

In an increasingly competitive global landscape, there is no denying the importance of relational databases to organizations these days. They are a great tool for controlling, analyzing, recording, storing and monitoring processes and transactions throughout all functional aspects of the organization. While the benefits provided by relational databases are instrumental to the overall operation of an organization, traditional databases still have their limitations. This is where SAP HANA comes in. SAP HANA is probably best described as new form of database that operates as an in-memory data platform that is capable of processing large amounts of data in real-time. With its capability to simultaneously handle both transaction processing

Analytics has been used as isolated initiatives within my company. Different levels of applications of analytics is a reality. Historically, quality department has leading the way in data-driven decision process by using several statistical and quality

To compete effectively in an era in which advantages are ephemeral, companies need to move beyond historical, rear-view understandings of business performance and customer behavior and become more proactive(tableau). Predictive Analytics is the use of data science for audience profiling. Generic audience profiling involves determining specific characteristics of your target audience and creating specific personas to represent each type of person within your target audience. Predictive analytics is essentially the same process, but from a data perspective (koozai). Predictive analytics can be used in wide areas in the industry, it’s importance is not constrained to a particular domain and ranges from marketing, telecommunication, retail, banking, etc. For example, the telecommunication industry has noticed a high customer churn since the switching costs are slim to none. So telecommunication companies operating in this industry are looking for new ways to differentiate themselves from competitors in order to retain customers. By using predictive analytics as a solution to this problem, they would be able to understand the customer needs, requirements and retain them also allowing them to acquire new ones more effectively. With predictive analytics, companies can predict trends, understand customers, improve business, drive strategic decision making and predict behavior. A company named Cox Communications, the third largest cable entertainment and broadband

The supply chain managers should also understand that data analytics is more than just one type of analytics. The first one is descriptive analytics; descriptive analytics will help the supply chain mangers in to know what really happens in supply chain. Descriptive analytics helps in data visualization and even in mapping. The next is the predictive analytics; this type of analytics helps the supply chain managers to use the available data in making very nice predictions. This

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

Define the required analytics through the manufacturers of statistical modeling. Using big data to analyze overall equipment effectiveness or calculate statistical process controls for quality defects to bolster techniques of problem solving solutions. Determine the required data sources by limiting teams as to what data they could look at based on storage or complexity of tying all of this data together. Identify internal data on processes of the key factors in determining the success of the new system. Ensuring trust in the data once the system is up and running which is smart to assign a time frame to remain on hand for any situations of data analytics that could cause a situation.

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.