Benefits to Company on Using Data Mining and Data Warehouse
Using current database company is providing web portal to the users of the system. For example person sitting in the main office can access information from the web portal currently what are the orders made by a particular sales man and what orders are ready to ship from warehouse. Same way warehouse person can access the orders that need to be shipped. Once the orders are ready warehouse staff can commits through the web portal to acknowledge main office.
This database provides general reports for. E.g. Daily Sales report by product or by customer or by route. These reports are helpful— particularly for real-time reporting —but they don’t allow in-depth analysis. The possibilities for reporting and analysis are endless. When it comes to analyzing data, a static list is insufficient. There’s an intrinsic need for aggregating, summarizing, and drilling down into the data. A data warehouse enables you to perform many types of analysis:
• Descriptive (what has happened)
• Diagnostic (why it happened)
• Predictive (what will happen)
• Prescriptive (what to do about it)
This is the level of analytics required to drive real quality, cost and process improvement in business. Mining and Warehouse Analysis in Detail
In order to provide the detail analytics, we tried to build another database (OLAP) on top of current database to provision them for analytical use. We follow the steps that are mention in the Red block of the
An active data warehousing, or ADW, is a data warehouse implementation that supports near-time or near-real-time decision making. It is featured by event-driven actions that are triggered by a continuous stream of queries that are generated by people or applications regarding an organization or company against a broad, deep granular set of enterprise data. Continental uses active data warehousing to keep track of their company’s daily progress and performance. Continental’s management team holds an operations meeting every morning to discuss how their
This data is collected and organized in order to process orders and maintain good customer service. The logical view of data would allow a knowledge worker to arrange and access information based on the needs of the business separating it from the physical view of how information is arranged and stored. The ability to do this allows for an employee to create detailed reports in order to determine information such as customer information and their order numbers and dates. This is imperative for a company like Comcast who has over 27 million customers in order to have a system to keep important data to analyze. Using a data warehouse allows them to gather from several databases and then the company can use the information to determine for example how many units of voice products are sold to create the necessary business intelligence to make future decisions and remain
One of the main functions of any business is to be able to use data to leverage a strategic competitive advantage. The use of relational databases is a necessity for contemporary organizations; however, data warehousing has become a strategic priority due to the enormous amounts of data that must be analyzed along with the varying sources from which data comes. Company gathers data by using Web analytics and operational systems, we must design a solution overview that incorporates data warehousing. The executive team needs to be clear about what data warehousing can provide the company.
The goals have been set and data analytics best practices need to be monitored. The experienced gained in this phase will shape the next course of action based on external and internal issues. As the data is formulated, it will identify the strengths and the weaknesses, threats and opportunities for improvements. Because the internal and external issues will continue
The latest technological development in data analytics and implementation helps organizations gain insights and how to deal with informed decisions.
What information is accessible? The data warehouse offers possibilities to define what’s offered through metadata, published information, and parameterized analytic applications. Is the data of high value? Data warehouse patrons assume reliability and value. The presentation area’s data must be correctly organized and harmless to consume. In terms of design, the presentation area would be planned for the luxury of its consumers. It must be planned based on the preferences articulated by the data warehouse diners, not the staging supervisors. Service is also serious in the data warehouse. Data must be transported, as ordered, promptly in a technique that is pleasing to the business handler or reporting/delivery application designer. Lastly, cost is a feature for the data
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
Companies are adopting business intelligence system within their organizations because by using the system reports they can gain the advantages of understanding their internal strength and weaknesses to face external competitors and challenges to increase profits and reduce cost on their everyday operations and processes.
A data warehouse is a large databased organized for reporting. It preserves history, integrates data from multiple sources, and is typically not updated in real time. The key components of data warehousing is the ability to access data of the operational systems, data staging area, data presentation area, and data access tools (HIMSS, 2009). The goal of the data warehouse platform is to improve the decision-making for clinical, financial, and operational purposes.
In this paper I am going to share my last company NTT DATA GLOBAL DELIVERY SERVICES LTD’s tactics, strategies, operations and management and its usage of analytics in the global market to achieve its goals.
The second pillar - enterprise-wide analytics - at ARI in my opinion is a work in progress. Analytics is managed by the new product development team; the team is responsible for deploying the new and latest technologies to our customers. Today, the data is centrally located in multiple Oracle databases with multiple universes used for reporting. Power users can develop reports accessing transactional tables instead of the universes. The end result can be getting different results in a report. This is not because the data is different but how users are requesting and interpreting the data. I refer to this pillar as a work in progress because we are currently working on a strategic multi-year project to build a warehouse to support reporting and analytics. One of the success factors of the project is to build a ‘single source of the truth’ for reporting. This new warehouse will have the business rules defined in the data – not an easy task requiring time and resources from the business areas. In my opinion, ARI does not have a formal business intelligence competency center (BICC) (Thomas H. Davenport, 2007, p. 29) but has taken the steps to create one. The warehouse project team includes resources from Information Technology and the different lines of business with key responsibilities to define the business rules for the data and take ownership of the data. A key improvement in this area would be to dedicate Information Technology resources to the project.
1. If I were to design Ben & Jerry’s data warehouse I would use several dimensions of information. The first dimension would consist of the company’s products; ice cream, frozen yogurt or merchandise. The marketing department has to know which products are selling, if Ben & Jerry’s didn’t know that their T-shirts are selling out as soon as they hit the stores, then they wouldn’t be able to take advantage of the opportunity to sell the shirts. The second dimension would consist of the different areas of sales; US, Canada, Mexico, or Europe. I am not sure if they sell their ice cream in Mexico, but with data collection they can find out if their ice cream would be a better seller in the hot climate,
Currently, the company has its own analytics team in sales and administration department, doing daily data analysis in order to improve the sales number in physical stores and the decision-making process of management.
A data warehouse (DW) can be acknowledged as one of the most complex information system modules available and it is a system that periodically retrieves and consolidates data from the sources into a dimensional or normalized data store. It is an integrated, subject-oriented, nonvolatile and a time-variant collection of data in support of management’s decisions (Inmon, 1993).
Data warehouse are multiple databases that work together. In other words, data warehouse integrates data from other databases. This will provide a better understanding to the data. Its primary goal is not to just store data, but to enhance the business, in this case, higher education institute, a means to make decisions that can influence their success. This is accomplished, by the data warehouse providing architecture and tools which organizes and understands the