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Data and Analytics Tutorial

Data and Analytics Overview
Under Construction

Data and Analytics Success

Data and Analytics Strategy
Project Management
Data Analytics Methodology
Quick Wins
Data Science Methodology

Requirements

BI Requirements Workshop

Architecture and Design

Architecture Patterns
Technical Architecture
Data Attributes
Data Modeling Basics
Dimensional Data Models

Enterprise Information Management

Data Governance
Metadata
Data Quality

Data Stores and Structures

Data Sources
Database Choices
Big Data
Atomic Warehouse
Dimensional Warehouse
Logical Data Warehouse
Data Lake
Operational Datastore (ODS)
Data Vault
Data Science Sandbox
Flat Files Data
Graph Databases
Time Series Data

Data Integration

Data Pipeline
Change Data Capture
Extract Transform Load
ETL Tool Selection
Data Warehoouse Automation
Data Wrangling
Data Science Workflow

BI and Data Visualization

BI - Business Intelligence
Data Viaulization

Data Science

Statistics
Descriptive Analytics
Predictive Analytics
Prescriptive Analytics

Test and Deploy

Testing
Security Architecture
Desaster Recovery
Rollout
Sustaining DW/BI

Data and Analytics Requirements

Business Intelligence and Data Warehousing Successful Programs are built on solid business requirements.

Data warehousing business requirements describe the needed solution in business terms.  Gathering and managing business requirements include these steps:

Business requirements are sometimes known as functional requirements and are the emphasis of this tutorial section.  Technical requirements, sometimes known as non-functional requirements, will be explained in the article Technical Architecture for Data Warehousing and Business Intelligence.

Rapid Data and Analytics Requirements Gathering

Gathering requirements rapidly using a sound methodology has numerous benefits:

Homework for Data Warehouse Requirements Gathering

 Be sure to do your homework before gathering requirements from others for the data warehouse and business intelligence effort.  You can save the time of the people you will meet with and interview before hand.  One thing you must understand is previous data warehousing efforts:

Researching documentation can help you get a handle on your organizations current and prior state of data warehousing.  You can examine documents such as:

In addition, computer based information can provide insight into requirements of existing systems:

 By doing your homework, you acknowledge the prior data warehousing efforts that have been made, avoid looking uninformed and save others time by not asking questions that have been previously addressed.

Identify Business Intelligence User Groups

  Identifying and engaging the right people who will participate in data warehousing and business intelligence efforts is key.  Focus on decision makers such as:

The poeple who analyze data are subject matter experts (SMEs) who will provide valuable input.  Examples are: 

The people who create reports often have great insights because they are asked by the business to create business intelligence reports.  They often have a backlog of requests and "wish lists" that can be translated to data warehousing requirements. 

 

Interview Data and Analytics Users

There are a number of good reasons to interview individual business intelligence users for data warehousing requirements gathering.  The reasons include:

Here are some suggestions to make the interview process productive:

Important Interview Questions

 

" I keep six honest serving men, They taught me all I knew;
Their names are what and why and when and how and where and who. "

- Rudyard Kipling




It is also important to understand the organization a higher level.  Peter Drucker in his book Management has recommended these critical questions and corresponding decisions:

Group Methods

A facilitated group session is often a great way to gather requirements.  Requirements are gathered faster than through the individual interview method and the meeting participants have the opportunity to bounce ideas off each other and reach a consensus on the requirements.

See the tutorial article, BI Requirements Workshop, for a practical approach to conducting group data warehouse requirement gathering sessions.

SMART Objectives

SMART Objectives Support Data Warehousing

 


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