Real Time Analytics For Different Software Applications Essay

In the case of real-time analysis dashboards have become very popular over the past five years they provide a view of key metrics to allow management by exception. Where post transaction data is being analyzed, data warehousing provides the ideal methodology for enhanced forecasting from the data. This also allows the ability to look for improvements in the supply chain, operations, and marketing to adjust processes and refine a message for marketing as part of a continuous improvement program.

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

Business analytics is done in real time so no wastage of time and results are generated for faster decision making.

In Competing on Analytics by Thomas Davenport and Jeanne Harris, the pillars of analytic completion are stated as: “(1) analytics supported a strategic, distinctive capability; (2) the approach to and management of analytics was enterprise-wide; (3) senior management was committed to the use of analytics; and (4) the company made a significant strategic bet on analytics-based competition” (Davenport & Harris, 2007, pp. 511-512) . This section will describe Aramark’s position within these pillars.

The book is all about the things that make one to be a smart consumer of cutting-edge analytics, facilitating to frame the judgement, questioning about the information and the procedure, operating to comprehend the consequences, and using them to progress results for his or her business. Even though it sounds direct, I directly acknowledged it as a deceptively single-minded set of purposes of the book. The writers planned the first half of the book about an analytics outline that entails of six stages: problem acknowledgment, evaluation of previous results, displaying, data assortment and data examination, and outcomes demonstration and action. This planned method to discerning about analytics is one of the most important notions that Davenport

In an uber globalized market of today, companies are faced with challenges in each and every step of their business. Our analytics and research services are geared towards giving those companies that extra edge over the competition. We process and analyze terabytes of data and break down all the fuzz and chatter around it to give our customers meaningful insights about their competition and the market they are engaged in.

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.

Predictive Analytics are able to help companies make sense of their historical data creating many potential advantages. Many organizations in the past have based decisions on what they believe to be true. They have had very little means to actually be able to know if they were making

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.

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

In the previous section, current traditional analytics capabilities and expertise were described as being the main analytics capabilities while in this section, the missing elements or elements that need to be more in line with the technical considerations of advanced analytics will be described for the three analytics pillars.

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.

In this paper, we describe how TCS is competing on analytics and applying it in its operations, how efficiently it is providing analytics as a service to its customers worldwide. We also talk about how TCS is using analytics to gain a competitive advantage, in what manner it is benefitting internally and externally from application of analytics and their progress so far.

Analytics and business intelligence (BI) are not new concepts in the market place, but the exponential growth of offerings, lower total cost of ownership (TCO), and simplified deployment options have made these solutions a necessity for modern businesses. Some customers continue to use a comprehensive stack of a database, extract-transfer-load (ETL) tools, an analytics engine, and a reporting interface from a single vendor, placing much of the burden on IT to keep operations running and produce reports. However, many businesses are finding success with a different model based on smaller-scale deployments of self-service or embedded analytics and data discovery tools directly to end users.

I still remember the day when my uncle mentioned about a drastic fall in the customer base of his corporate library solution and as a result, they collected feedback from customers and developed a more user-friendly interface for Kwench library solution*. As a result, more people started using the application. Currently, the company has more than 150 corporate clients and has been mentioned in Forbes India magazine as one of the emerging startups. It was at this point I realized how information technology and data analysis could be used to solve real-time business problems. This exposure had created a lasting impact on me. I learned that data analysis plays a pivotal role in making informed business decisions, solve complex