Enterprise Data Warehouse

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Enterprise Data Warehouse

Pressured to maximize enterprise data warehouse return on investment and want practical suggestions to help reduce costs and deliver projects faster?

What is an enterprise data warehouse?

There are many definitions! Think of a data warehouse as a central storage facility which collects information from many sources, manages it for efficient storage and retrieval, and delivers it to many audiences, usually to meet decision support and business intelligence requirements.

Remember the days before we had computers? Enterprise Data Warehouse

Information was stored in file folders or sometimes forgotten in desk drawers.

It was never available in the right hands at the right time to make the right decision until records management was introduced and central filing systems were established.

These central-filing systems gathered information from everyone (many sources), managed it for efficient storage and retrieval, and delivered it to many audiences for analysis purposes.

These central-filing systems helped minimize duplication of data and went a long way towards eliminating problems finding files that were lost on some-one’s desk while they took an extended winter vacation.

They also helped reduce information storage requirements as they eliminated the need for many filing cabinets, in many departments to hold duplicate files.

These central filing systems were governed by records management experts who took ownership for establishing records management principles, file storage design, file management processes, security, and cataloging to ensure easy file retrieval.

Data warehousing is similar to central records management!

A data warehousing solution requires data warehouse management which is:

A set of policies; standards, best practices and processes needed to organize and control the collection, management and distribution of information required for management and business intelligence purposes; and
Operational management processes to control system processes and process architecture.

Architecture is normally the responsibility of a data warehouse architect who is responsible for overall management including responsibility for:

Introducing data warehouse basics to all users;

Defining enterprise data warehouse principles to guide design and use;

Specifying database design and database schema management, to ensure efficient data storage;

Architecture and design, which includes all of the procedures and processes required to collect data, store it and distribute it;

Data warehouse management, which includes all system processes required to load data efficiently and manage errors effectively;

Data Warehouse security, which includes ensuring that effective database backup and data recovery protection processes have been implemented and fully tested;

Establishing data mining warehouse policies to ensure that overall performance is not impacted;

Defining database partitioning strategies to help ensure efficient loading, storage and retrieval;

Metadata management to ensure proper cataloging and definition of data store din the warehouse;

Data mart usage policies to ensure effective distribution of data and reduce the potential duplication key data structures; and

Ensuring the operational service level agreement is achieved.

Enterprise data warehouse architecture considerations

A typical warehouse might load many millions of records per day—It involves extracting data from many source systems, verifying data quality, cleansing the data in some cases, loading it into staging areas for initial processing, moving it from staging to the warehouse and then moving it into data marts, and sometimes aggregating the data to help reporting performance.

In addition, data must be purged from the warehouse when it reaches its retention period and backup must occur with no interruption to availability or performance.

There are a lot of moving parts and it is very important that overall design consider all significant data warehouse ETL factors to ensure efficient storage and effective use of the data.

Enterprise data warehouse checklist

An enterprise data warehouse will need to address most of the following topics:

Benefits of a data warehouse;

Build data warehouse;

Building a data warehouse;

Building data warehouses;

Business data intelligence warehouse;

Business requirements data warehouse project;

Characteristics of data warehouse;

Corporate data warehouse;

CRM data warehouse;

Customer data warehouse;

Data intelligence warehouse;

Data management project warehouse;

Data management system warehouse;

Data management warehouse;

Data mining data warehouse;

Data security warehouse;

Data storage warehouse;

Data warehouse administration;

Data warehouse administrators;

Data warehouse analyst;

Data Warehouse basics;

Data warehouse and business intelligence;

Data warehouse and CRM;

Data warehouse and data mart;

Data warehouse and data mining;

Data warehouse and marts;

Data warehouse and mining;

Data warehouse and OLAP;

Data warehouse appliances;

Data warehouse applications;

Data warehouse architectures;

Data warehouse backup;

Data warehouse benefits;

Data warehouse best practices;

Data warehouse business intelligence;

Data warehouse business requirement templates;

Data warehouse business requirements project;

Data warehouse careers;

Data warehouse cleansing;

Data warehouse concepts;

Data warehouse construction;

Data warehouse consultancy;

Data warehouse consultants

Data warehouse consulting;

Data warehouse CRM;

Data warehouse data mart;

Data warehouse data mining;

Data warehouse data model;

Data warehouse data modeling;

Data warehouse databases;

Data warehouse decision support system;

Data warehouse design and development;

Data warehouse design solution;

Data warehouse designs;

Data warehouse development;

Data warehouse dimension models;

Data warehouse environments;

Data warehouse experts;

Data warehouse glossary of terms;

Data warehouse hardware;

Data warehouse information;

Data warehouse integration

Data warehouse jobs;

Data warehouse lead;

Data warehouse lifecycle;

Data warehouse loading;

Data warehouse management project;

Data warehouse managers;

Data warehouse metadata;

Data warehouse methodology;

Data warehouse mining;

Data warehouse model;

Data warehouse modeling;

Data warehouse models;

Data warehouse monitoring;

Data warehouse offshoring;

Data warehouse performance;

Data warehouse personnel;

Data warehouse planning;

Data warehouse problems;

Data warehouse process;

Data warehouse professionals;

Data warehouse program;

Data warehouse project plan;

Data warehouse projects;

Data warehouse report;

Data warehouse requirements;

Data warehouse resources;

Data warehouse roles and responsibilities;

Data warehouse salary;

Data warehouse services;

Data warehouse skills;

Data warehouse software;

Data warehouse solutions;

Data warehouse specialist;

Data warehouse star schema;

Data warehouse strategies;

Data warehouse strategy;

Data warehouse support;

Data warehouse systems;

Data warehouse technology;

Data warehouse terminology;

Data warehouse tools;

Data warehouse tuning;

Data warehouse users;

Data warehouse vs data mart;

Data warehouses and data marts;

Data warehouses and data mining;

Data warehouses non technical issues;

Data warehousing;

Data warehousing and data mining;

Database and data warehouse;

Database design;

Database development software;

Databases and data warehouses;

Design plan for data warehouse;

Enterprise data warehouse solutions;

Estimates for creating data warehouse;

Estimating building a data warehouse;

ETL and data warehouse;

Improving data warehouse and business;

Information data warehouse;

IT project plan data warehouse;

Jobs in data warehouse;

Making data warehouses;

Management data warehouse;

Open source data warehouse;

Open sourced data warehouse;

Operational data warehouse;

Outsourcing offshore data warehouse;

Quality data warehouse;

Rapid data warehouse design;

Real time data warehouse;

Security data warehouse;

Standards for a data warehouse;

Teradata data warehouse;

The advantages of data warehouse;

Types of data warehouse;

Warehouse data; and

Warehouse data management,

Enterprise Data Warehouse--summary...

Information management is a discipline that governs accountability for the structure and design, storage, movement, security, quality, delivery and usage of information required for management and business intelligence purposes.

Enterprise data warehouse standards, best practices and a data management plan are critical to ensure effective and efficient storage, movement and delivery of information.

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