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Data Warehousing and Business Intelligence - Coggle Diagram
Data Warehousing and Business Intelligence
Introduction
Business Drivers
Data warehouses are used to support operational functions, compliance requirements and artificial intelligence activities
Data warehouses have the ability to store historical data
Business intelligence is the main reason to have a data warehouse
Goals and Principles
Support Business Intelligence activity
Enable effective business analysis and decision-making
Find ways to innovate based on insights from their data
Essential Concepts
Business Intelligence (BI): involves analyzing organizational data to gain insights about products, services, and customers, and improve decision-making.
Data Warehouse: is a combination of an integrated decision support database and related software programs used to collect, cleanse, transform and store data from a variety of operational and external sources.
Data warehousing is the process of extracting, cleansing, transforming, controlling and loading data into a data warehouse to enable an integrated and historical business context for operational data.
There are two main approaches to the construction of data warehouses led by Bill Inmon and Ralph Kimball
Data Warehouse emerged in the 1980's era
Is a process of planning, implemention and control for reporting, query and analysis.
Activities
Understand Requirements
Differences between developing a data warehouse and an operating system
Define and Maintain the DW/BI Architecture
Describes the origin, destination, timing, reason and method of data storage.
Technical Architecture
Management Processes
Develop the Data Warehouse and Data Marts
Data
Technology
Business Intelligence tools
Map sources
Remediate and transform data
Populate the Data Warehouse
Data preparation and processing are the largest part of DW/BI efforts
Design decisions and the principles of what data the DW should contain are a key priority
Implement the Business Intelligence Portfolio
To implement the BI Portfolio is to identify the right tools for the user communities
Maintain Data Products
An implemented warehouse and its BI tools are a data product.
Tools
Metadata Repository
Large organizations have tools from different vendors and different versions.
Data Integration Tools
Process audit, control, restart, and scheduling
The ability to selectively extract data
Business Intelligence Tools Types
Operational reporting
Business performance management (BPM)
Descriptive, self-service analytics
Techniques
Prototypes to Drive Requirements
Rapidly prioritize requirements prior to the start of implementation activities
Data virtualization technology can alleviate some of the traditional implementation pains
Self-Service BI
Is a key delivery channel within the BI portfolio.
A controlled portal channels user activity
Visualization and statistical analysis tools enable rapid data exploration and discovery
Audit Data that can be Queried
Lineage maintenance is important in structures and processes.
Allowing users to view this audit information improves user confidence
Implementation Guidelines
Readiness Assessment / Risk Assessment
Define data sensitivity and security constraints
Perform tool selection
Secure resources
Create an ingestion process to evaluate and receive source data
Release Roadmap
Data warehouses are built incrementally.
It is important to have a flexible and adaptive development and maintenance plan.
Configuration Management
Configuration management aligns with launch roadmap
Provides scripts to automate development, testing and transport to production
Organization and Cultural Change
Business sponsorship
Business goals and scope
• Business resources
Business readiness
Vision alignment
DW/BI Governance
Enabling Business Acceptance
Conceptual Data Model
Data quality feedback loop
End-to-end Metadat
End-to-end verifiable data lineage
Customer / User Satisfaction
Customers must understand the data and the operations team must respond to identified issues.
Service Level Agreements
SLAs should specify business and technical expectations for the environments
Reporting Strategy
Access security to ensure that only authorized users can access sensitive data.
Metrics
Usage Metrics, subject area coverage porcentages