Analysis Of The Proposed Solution, And The Obtained Results With Bigs Essay

Target Corporation allocated large budget to upgrade information system as part of a roadmap to transform business (Target Roadmap, 2015). Once the upgrade is completed, it will provide a large amount of intelligent data for internal resources to support customers faster. It further tracks performance and controls accurately the timely information about daily operations in real time. The automated online and on-demand ad-hoc reports generate reports for each store any time as well retains records of products and services.

As we discuss the possibility of emerging into business intelligence software we must keep in mind the overall purpose of using any type of software is to reach strategic goals in order to increase market shares. I will discuss how business intelligence software will allow us to meet those strategic goals. We will establish what type of information and analysis capabilities will be available once this business intelligence software is implemented. We will discuss hardware and system software that will be required to run specific business intelligence software. Lastly, I will give a brief synopsis on three vendors (IBM, Microsoft Microsoft and Oracle) that are dominating the business information software

Business organizations receive different types data, from different sources, in the form of sales records, customer databases,

Business intelligence (BI) merges architectures, tools, databases, analytical tools, applications, and methodologies. It also is context free like DSS. BI deduces the connections between business entities by evaluating copious volumes of historical data which supports decisions. BI has four major components consisting of a data warehouse, business analytics, business performance management, and a user interface.

The enterprise data repository (EDR) project at InsuraCorp was developed to be the data warehouse for customer and product data for all InsuraCorp business units. There is a school of thought that data management responsibilities should fall to IT and to the business units themselves. The collaboration between the IT and business users together could produce higher quality data and administer data management more effectively. Everyone who receives or accesses information within an organization is responsible for data integrity so it only stands to reason all parties have a responsibility. Both the information system managers and the business managers, as data stewards, are duty-bound to monitor and control data accuracy. With data, it is as important to have accurate input so that the information that is shared will be useful to other users. Storing data in a holding tank will not solve a bad data problem.

In detail, a strong resistance will come from some of the operating companies that already have “their own small-scale business intelligence applications in place”. These companies may not see any valid reason or advantage to switch and implement a new software system. Furthermore, another obstacle that SYSCO might confront will be the objection from the existing managers and IT experts averse and incapable of using a new software with different functions. Moreover, the forthcoming implementation time of the BI software proposed by the Assistant Vice President of Technology and Applications Twila Day might raise doubts and concerns among management as well as

Loblaw used to save store and vendor information in different types of Legacy systems, for example, the vendors’ sales data is stored in the system called Bi-query, and the vendor stores payment records can be found in Customer Information Control System (CICS). However, given the size and complexity of Loblaw, it is hard to remain competitive without a system that can integrate information from all business areas and provide real-time information updates of critical information so that an entire enterprise may function as one. Therefore, Loblaw starts to transfer store and vendor data from Legacy systems, into a more efficient and powerful system called SAP.

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

Q3: While this case study supports a specific data warehouse product, please locate another case study from another data warehousing Software Company and explain the data warehouse that was designed in that case study?

The facts have shown when changes are planned to integrate with the existing systems slowly replacing the outdated process with a more productive one the business functions do improve. IT

In the organizational layer, DLL has a global business intelligence and global analytics team. The business intelligence team’s focus is data warehousing, dashboard designing and providing real-time data companywide for all the countries, which can be queried via SQL or Hyperion. Given that data often needs clean up and analysis to better understand its trends, the business intelligence team has created a Virtual Reporting Tool which is accessible by all members of the company and is meant to be the only source of the truth. This tool provides live reports and dashboards which are used for monitoring purposes and for analysis. On the other hand, the global analytics team’s focus is

Implemented innovation solutions (minor system enhancements and small projects) that increased electronic activity for exchanging business documents from paper to digital, reducing cost, growing revenue and boosting productivity.

In your business, you have your own big data challenges. You have to turn heaps of data about various entities into actionable information. The reporting needs of institutions have evolved from simple single subject queries to data discovery and enterprise-wide analysis that tells a complete story across the institution. While the volume, variety and velocity of big data seem overwhelming, big data technology solutions hold great promise. The way I see it we can use this as one of the biggest asset for the company. We have the capacity to see patterns recounting in real time across complex systems. Huron is marshalling its resources to bring smarter computing to big data. With the Huron big data platform, we are enabling our clients to manage data in ways that were never thought possible before.

Design, code and deliver user friendly multi-tier business intelligence solutions that utilize data warehouse/data mining technologies to consume data across various database platforms and data stores.

R.L Fielding (2008) reiterates that Business Intelligence is a thorough and holistic analysis of the company records, data, information, and software application for effective decision making. All decision making processes need an organized, readily-accessible, and human readable compilations of data. With the use of an effective tool the firm can easily figure out their own business processes, the behavior of their customers, and the economic trend of the industry. With these facts, the firm can arrive at a better strategy to achieve their specified goals with confidence.