Combining these logs with traditional business data, organizations are able to examine the impact of their e -business and develop appropriate strategies. Oracle9 i as clickstream Intelligence is the web-based e -business intelligence solution that allows you to collect data from these web site activities and facilitates the acquisition, analysis, and reporting on Web interactions with customers, suppliers, and employees. Oracle9 i application Server to begin to understand Oracle9 i as clickstream Intelligence, you must first examine the architecture in which needed it participates. Oracle9 i as is a comprehensive and integrated application server providing an integrated solution built on the Oracle9 i e -business Intelligence platform that manages the technical complexity of assembling a complete middle tier Internet infrastructure. Oracle9 i as components include: Oracle http server powered by Apache providing enterprise-wide consistency and flexibility to support site growth. Oracle Enterprise manager (OEM) deploying Lightweight Directory Access Protocol or ldap, a single sign on and Secure socket layer technology, to manage and secure the web infrastructure. A fully integrated J2EE compliant platform providing a basic Web server, which allows you to develop and deploy java and Enterprise Edition (J2EE) applications, which use simple Object Access Protocol (soap) Oracle web Cache to cache data and accelerate performance on any web site.
Determining the best time for maintenance and backups. Detecting traffic growth trends which will allow you to plan for future infrastructure needs. Determining which search engine to implement. Purpose, this module introduces you to Oracle9 i, as clickstream Intelligence and Web server/Web log concepts. Oracle9 i, application Server (Oracle9 i, as oracle9 i, developer suite (Oracle9 i, ds and Oracle9 i, as clickstream Intelligence relationships are discussed through architecture diagrams and descriptions. Module Objectives, after completing this module, you will be able to: Describe the role of Oracle9 i as clickstream Intelligence as an integrated component of Oracle9 i as business Intelligence Explain the architecture and components of Oracle9 i as clickstream Intelligence Understand Oracle9. Web servers store these clicks in the form of Web logs. This information is then stored in databases and analyzed for every web site, web page, and newsgroup visited.
Other Dimensions Categorical dimensions: generated groups (additional key components) Partitioning dimensions: subtypes (planned. Actual) Informational dimensions: generate different types of data (messy). Administering a web site using Oracle9ias clickstream Intelligence. Module Objectives, purpose, this module describes how to deploy oracle9 i, as clickstream Intelligence. You glean necessary skills using this Web-based, e -business Intelligence solution that enables you to create and modify data sources for Web logs for the mycompany web site, which provide an integrated extensible solution for measuring Web traffic and improving Web site effectiveness.
Prerequisites, before starting this module, you must: Complete the, install the Oracle9 i, application Server module including either the business Intelligence or Unified Messaging component. Understand data warehouse development methodology, be familiar with web server technology. Have a technical understanding of information storage and retrieval. Reference material, the following is a list of useful reference material if you want additional information about the topics in this module: Documentation: Oracle9 i, as clickstream Intelligence Administration guide e, class: D12847GC10 - oracle9 i, as clickstream Intelligence Administration, scenario. You are a web Master for mycompany's corporate headquarters in New York city. You are the technical expert responsible for ensuring that the site is running smoothly. Some of the challenges that you face on a regular basis are: Detecting short broken links and invalid resource types.
This step reflects the information and analytical characteristics of the data warehouse. Translate this into the physical model. This reflects the changes necessary to reach the stated performance objectives. The business Model Identify the data structure, attributes and constraints for the clients data warehousing environment. Stable Optimized for update Flexible business Model As always in life, there are some disadvantages to 3NF: Performance can be truly awful.
Most of the work that is performed on denormalizing a data model is an attempt to reach performance objectives. The structure can be overwhelmingly complex. We may wind up creating many small relations which the user might think of as a single relation or group of data. Structural Dimensions The first step is the development of the structural dimensions. This step corresponds very closely to what we normally do in a relational database. The star architecture that we will develop here depends upon taking the central intersection entities as the fact tables and building the foreign key primary key relations as dimensions.
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Statistical Analysis, data discovery. (decision support, artificial intelligence and expert systems). Olap, data visualization, hardware budget, a typical startup warehouse project allocates more than 60 percent of using its budget for hardware and software to the creation of a powerful storage component, spending just 30 percent on data mining and user access technologies. Systems Analysis Budget Budgeting for systems analysis and development, however, follows a very different pattern. More than 50 percent of development dollars are spent on building acquisition capabilities, 30 percent fund the development of user solutions and 20 percent are dedicated to the creation of databases in the storage component. Design Issues Relational and Multidimensional Models Denormalized and indexed relational models more flexible multidimensional models simpler to use and more efficient Star Schemas in a rdbms in most dissertation companies doing rolap, the dbas have created countless indexes and summary tables in order to avoid I/O-intensive. As the indexes and summary tables proliferate in order to optimize performance for the known queries and aggregations that the users perform, the build times and disk space needed to create them has grown enormously, often requiring more time than is allotted and more space. Building a data warehouse from a normalized Database The steps develop a normalized entity-relationship business model of the data warehouse. Translate this into a dimensional model.
Or Informix Software Inc. Specialized hardware symmetric multiprocessor (SMP) or massively parallel processor (MPP) machines. Storage, the majority of warehouse storage today is being managed by relational databases running on Unix platforms. Oracle, sybase Inc., ibm corp. And Informix control 65 percent of the warehouse storage market. Access, different end-user PCs and workstations draw data from the warehouse with the help of multidimensional analysis products, neural networks, data discovery tools or analysis tools. These powerful, "smart" software products are the real driving force behind the viability of data warehousing. Access tools, intelligent Agents and Agencies, query facilities and Managed query Environments.
it means. Clean and prepare the data. Extract from legacy files and reformat to make it usable. Transport data from one location to another. Storage, the storage component holds the data so that the many different data mining, executive information and decision support systems can make use of it effectively. The Storage Area, managed by, relational databases like those from Oracle corp.
Data Acquisition Data Storage data a access. Handles acquisition of data from legacy wallpaper systems and outside sources. Copyright Complaint Adult Content Flag as Inappropriate. I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described. Download Presentation, an Image/Link below is provided (as is) to download presentation. Download Policy: Content on the website is provided to you as is for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
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Hrsa has thousands of active grants worth billions of dollars to improve and expand health william care services for underserved people, focusing on the following program areas: health Professions, healthcare systems, hiv/aids, maternal and Child health, Office of the Administrator, Organ Donation, Primary health Care/Health Centers. An active grant is a grant whose project period end date is beyond the current date. Grants can be active whether or not they have received an award funding in the current fiscal year. The hrsa data warehouse (HDW) allows users to interact with data in charts, tables/reports, maps, and tools. Data sources and Refresh Dates page for more information about where grants data is available in the data warehouse. Download, skip this Video, loading SlideShow in 5 Seconds. Designing a data warehouse powerPoint Presentation. Download Presentation, designing a data warehouse 1 / 21, designing a data warehouse. Issues in dw design.