Data Warehousing for Business Intelligence Specialization

Start Date: 09/15/2019

Course Type: Specialization Course

Course Link: https://www.coursera.org/specializations/data-warehousing

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About Course

Evaluate business needs, design a data warehouse, and integrate and visualize data using dashboards and visual analytics. This Specialization covers data architecture skills that are increasingly critical across a broad range of technology fields. You’ll learn the basics of structured data modeling, gain practical SQL coding experience, and develop an in-depth understanding of data warehouse design and data manipulation. You’ll have the opportunity to work with large data sets in a data warehouse environment to create dashboards and Visual Analytics. You will use of MicroStrategy, a leading BI tool, OLAP (online analytical processing) and Visual Insights capabilities to create dashboards and Visual Analytics. In the final Capstone Project, you’ll apply your skills to build a small, basic data warehouse, populate it with data, and create dashboards and other visualizations to analyze and communicate the data to a broad audience.

Course Syllabus

Database Management Essentials
Data Warehouse Concepts, Design, and Data Integration
Relational Database Support for Data Warehouses
Business Intelligence Concepts, Tools, and Applications

Deep Learning Specialization on Coursera

Course Introduction

Data Warehousing for Business Intelligence Specialization-

Course Tag

Pentaho Data Visualization (DataViz) 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.
Semantic warehousing Data warehousing contributed to companies' business values and lots of solutions and tools are commercially successful. Analysis of internal data delivers a certain level of business values, on the contrary to this Semantic warehousing environment has not yet matured. Capacity of social data is increasing rapidly and various efforts of finding value from that data are made widely known as Big data, etc. Semantic warehousing can be the mainstream of treat data and intelligence of social world in the future though it is defined with other keywords.
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 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 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.
Business intelligence To distinguish between the concepts of business intelligence and data warehouses, Forrester Research defines business intelligence in one of two ways:
Business intelligence Business intelligence and business analytics are sometimes used interchangeably, but there are alternate definitions. One definition contrasts the two, stating that the term business intelligence refers to collecting business data to find information primarily through asking questions, reporting, and online analytical processes. Business analytics, on the other hand, uses statistical and quantitative tools for explanatory and predictive modelling.
Business intelligence Often, scenarios revolve around distinct business processes, each built on one or more data sources. These sources are used by features that present that data as information to knowledge workers, who subsequently act on that information. The business needs of the organization for each business process adopted correspond to the essential steps of business intelligence. These essential steps of business intelligence include but are not limited to:
Semantic warehousing At the Big data era, semantic processing is going to become major IT process. Semantic warehousing is digital infra of Intelligence.
Business intelligence Therefore, when designing a business intelligence/DW-solution, the specific problems associated with semi-structured and unstructured data must be accommodated for as well as those for the structured data.
Real-time business intelligence The speed of today's processing systems has moved classical data warehousing into the realm of real-time. The result is real-time business intelligence. Business transactions as they occur are fed to a real-time BI system that maintains the current state of the enterprise. The RTBI system not only supports the classic strategic functions of data warehousing for deriving information and knowledge from past enterprise activity, but it also provides real-time tactical support to drive enterprise actions that react immediately to events as they occur. As such, it replaces both the classic data warehouse and the enterprise application integration (EAI) functions. Such event-driven processing is a basic tenet of real-time business intelligence.
Data classification (business intelligence) In business intelligence, data classification has close ties to data clustering, but where data clustering is "descriptive", data classification is "predictive". In essence data classification consists of using variables with known values to predict the unknown or future values of other variables. It can be used in e.g. direct marketing, insurance fraud detection or medical diagnosis.
Semantic warehousing In data management, semantic warehousing is a methodology of digitalized text data using similar functions to Data warehousing (DW), such as ETL(Extract, transform, load), ODS(Operational data store), and MODEL. Key value operation is less useful for the digitalized text. Semantic warehousing is different from DW in that semantic information base from text(semantic) data.
Business intelligence Business intelligence can be used to support a wide range of business decisions ranging from operational to strategic. Basic operating decisions include product positioning or pricing. Strategic business decisions include priorities, goals and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company sources internal to the business such as financial and operations data (internal data). When combined, external and internal data can provide a more complete picture which, in effect, creates an "intelligence" that cannot be derived by any singular set of data. Amongst myriad uses, business intelligence tools empower organisations to gain insight into new markets, assess demand and suitability of products and services for different market segments and gauge the impact of marketing efforts.
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.
Mobile business intelligence Mobile Business Intelligence (Mobile BI or Mobile Intelligence) is defined as “The capability that enables the mobile workforce to gain business insights through information analysis using applications optimized for mobile devices” Verkooij(2012) Business intelligence (BI) refers to computer-based techniques used in spotting, digging-out, and analyzing business data, such as sales revenue by products and/or departments or associated costs and incomes.
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.
Semantic warehousing Semantic warehousing will be equally or more important than data warehousing in the future.
Visual business intelligence Visual Business Intelligence (VBI) is knowledge based on the application of visual data to a business problem or opportunity.
Business intelligence The quality aspect in business intelligence should cover all the process from the source data to the final reporting. At each step, the quality gates are different: