Design and Build a Data Warehouse for Business Intelligence Implementation

Start Date: 05/31/2020

Course Type: Common Course

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About Course

The capstone course, Design and Build a Data Warehouse for Business Intelligence Implementation, features a real-world case study that integrates your learning across all courses in the specialization. In response to business requirements presented in a case study, you’ll design and build a small data warehouse, create data integration workflows to refresh the warehouse, write SQL statements to support analytical and summary query requirements, and use the MicroStrategy business intelligence platform to create dashboards and visualizations. In the first part of the capstone course, you’ll be introduced to a medium-sized firm, learning about their data warehouse and business intelligence requirements and existing data sources. You’ll first architect a warehouse schema and dimensional model for a small data warehouse. You’ll then create data integration workflows using Pentaho Data Integration to refresh your data warehouse. Next, you’ll write SQL statements for analytical query requirements and create materialized views to support summary data management. Finally, you will use MicroStrategy OLAP capabilities to gain insights into your data warehouse. In the completed project, you’ll have built a small data warehouse containing a schema design, data integration workflows, analytical queries, materialized views, dashboards and visualizations that you’ll be proud to show to your current and prospective employers.

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Course Introduction

Design and Build a Data Warehouse for Business Intelligence Implementation With the explosion of Big Data in the world, it is critical for business intelligence requirements to be able to design and build data warehouses to store and process the data for analytic and decision making purposes. This course gives you a hands-on approach to designing and building data warehouses that can support your business intelligence requirements while also providing you with a high level of confidence in design and build data warehouses for your business requirements. After completing this course, you will be able to: 1. Design and build a data warehouse 2. Design and build a data warehouse to support your business intelligence requirements 3. Design and build a data warehouse for your business requirements. 4. Use design and build data warehouses to store and process the data for analytic and decision making purposes 5. Use design and build new data warehouses to support your business requirements 6. Use design and build a new data warehouse for your business requirements. This course is part of the iMBA offered by the University of Illinois, a flexible, fully-accredited online MBA at an incredibly competitive price. For more information, please see the Resource page in this course and 1: Business Intelligence & Data Warehouses Module 2: Business Intelligence & Data Visualization Module 3: Business Intelligence & Data Integration Designing a Data Analytics Strategy In this course you will learn how to

Course Tag

Data Warehousing Microstrategy Data Warehouse SQL

Related Wiki Topic

Article Example
Business intelligence or as "BIDW". A data warehouse contains a copy of analytical data that facilitates decision support. However, not all data warehouses serve for business intelligence, nor do all business intelligence applications require a data warehouse.
Data warehouse In the "bottom-up" approach, data marts are first created to provide reporting and analytical capabilities for specific business processes. These data marts can then be integrated to create a comprehensive data warehouse. The data warehouse bus architecture is primarily an implementation of "the bus", a collection of conformed dimensions and conformed facts, which are dimensions that are shared (in a specific way) between facts in two or more data marts.
Oracle Warehouse Builder Oracle Warehouse Builder (OWB) is an ETL tool produced by Oracle that offers a graphical environment to build, manage and maintain data integration processes in business intelligence systems.
Designbuild A 2011 study analyzing the designbuild project delivery method in the United States shows designbuild was used on about 40 percent of non-residential construction projects in 2010, a ten percent increase since 2005. The study was commissioned by the Design-Build Institute of America (DBIA) and was completed by RSMeans Reed Construction Data Market Intelligence.
Data warehouse This definition of the data warehouse focuses on data storage. The main source of the data is cleansed, transformed, catalogued and made available for use by managers and other business professionals for data mining, online analytical processing, market research and decision support. However, the means to retrieve and analyze data, to extract, transform, and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata.
Business intelligence software Business intelligence software is a type of application software designed to retrieve, analyze, transform and report data for business intelligence. The applications generally read data that have been previously stored, often, though not necessarily, in a data warehouse or data mart.
Data warehouse In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis, and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place and are used for creating analytical reports for knowledge workers throughout the enterprise. Examples of reports could range from annual and quarterly comparisons and trends to detailed daily sales analysis.
Business intelligence A Business Intelligence portal (BI portal) is the primary access interface for Data Warehouse (DW) and Business Intelligence (BI) applications. The BI portal is the user's first impression of the DW/BI system. It is typically a browser application, from which the user has access to all the individual services of the DW/BI system, reports and other analytical functionality.
Data warehouse A hybrid DW database is kept on third normal form to eliminate data redundancy. A normal relational database, however, is not efficient for business intelligence reports where dimensional modelling is prevalent. Small data marts can shop for data from the consolidated warehouse and use the filtered, specific data for the fact tables and dimensions required. The DW provides a single source of information from which the data marts can read, providing a wide range of business information. The hybrid architecture allows a DW to be replaced with a master data management repository where operational, not static information could reside.
Real-time business intelligence RTBI is an approach in which up-to-a-minute data is analyzed, either directly from operational sources or feeding business transactions into a real time data warehouse and Business Intelligence system.
Data warehouse automation Data warehouse automation works on the principles of design patterns. It comprises a central repository of design patterns, which encapsulate architectural standards as well as best practices for data design, data management, data integration, and data usage.
Business intelligence When planning for business data and business intelligence requirements, it is always advisable to consider specific scenarios that apply to a particular organization, and then select the business intelligence features best suited for the scenario.
Data warehouse A key advantage of a dimensional approach is that the data warehouse is easier for the user to understand and to use. Also, the retrieval of data from the data warehouse tends to operate very quickly. Dimensional structures are easy to understand for business users, because the structure is divided into measurements/facts and context/dimensions. Facts are related to the organization's business processes and operational system whereas the dimensions surrounding them contain context about the measurement (Kimball, Ralph 2008). Another advantage offered by dimensional model is that it does not involve a relational database every time. Thus, this type of modeling technique is very useful for end-user queries in data warehouse.
Business intelligence Though the term business intelligence is sometimes a synonym for competitive intelligence (because they both support decision making), BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors. If understood broadly, business intelligence can include the subset of competitive intelligence.
Data warehouse The "top-down" approach is designed using a normalized enterprise data model. "Atomic" data, that is, data at the greatest level of detail, are stored in the data warehouse. Dimensional data marts containing data needed for specific business processes or specific departments are created from the data warehouse.
Data warehouse The data vault modeling components follow hub and spokes architecture. This modeling style is a hybrid design, consisting of the best practices from both third normal form and star schema. The data vault model is not a true third normal form, and breaks some of its rules, but it is a top-down architecture with a bottom up design. The data vault model is geared to be strictly a data warehouse. It is not geared to be end-user accessible, which when built, still requires the use of a data mart or star schema based release area for business purposes.
Business Intelligence Competency Center Since finance and energy industries have successfully implemented business intelligence competency centers (BICCs) and have produced financial returns on their investment and accelerated decision-making speed, the healthcare industry is initiating use of BICCs. Creating a business intelligence competency center in healthcare involves prioritizing information needs, creating data governance structures, identifying data stewards to provide data quality assurance, establishing ongoing education programs, and defining predictive modeling, analytics, data warehouse, and cloud storage tools.
Designbuild Although the Design-Build Institute of America (DBIA) takes the position that designbuild can be led by a contractor, a designer, a developer or a joint venture, as long as a designbuild entity holds a single contract for both design and construction, some architects have suggested that architect-led designbuild is a specific approach to designbuild.
Designbuild Proponents of designbuild counter that designbuild saves time and money for the owner, while providing the opportunity to achieve innovation in the delivered facility. They note that value is added because design-build brings value engineering into the design process at the onset of a project. Designbuild allows the contractor, engineers and specialty trade contractors (subcontractors) to propose best-value solutions for various construction elements before the design is complete. Designbuild brings all members of a project team together early in the process to identify and address issues of cost, schedule and constructability. Proponents suggest that as a result, design-build alleviates conflict between architects and contractors and reduces owner risk for design errors. They argue that once design is finalized and construction begins, the greatest opportunity to achieve cost savings has already been lost, and the potential for design errors is greater, leading to change orders that create cost growth and schedule delays. Proponents note that designbuild allows owners to avoid being placed directly between the architect/engineer and the contractor. Under design–bid–build, the owner takes on significant risks because of that position. Designbuild places the responsibility for design errors and omissions on the design–builder, relieving the owner of major legal and managerial responsibilities. The burden for these costs and associated risks are transferred to the designbuild team.
Business intelligence To distinguish between the concepts of business intelligence and data warehouses, Forrester Research defines business intelligence in one of two ways: