What Is a Data Warehouse?
Let me tell you directly: a data warehouse is the secure electronic storage of information by a business or other organization. The goal here is to build a collection of historical data that you can retrieve and analyze to gain useful insights into your operations.
You should know that a data warehouse is a key part of business intelligence. This broader concept covers the information infrastructure that modern businesses use to track past successes and failures and guide future decisions.
How a Data Warehouse Works
Understand that the need for data warehousing came about as businesses started relying on computer systems for creating, filing, and retrieving important documents. The concept was introduced in 1988 by IBM researchers Barry Devlin and Paul Murphy.
A data warehouse is built to enable analysis of historical data. By comparing data from multiple sources, you get insights into company performance. It's designed for running queries and analyses on historical data from transactional sources.
Once data is added to the warehouse, it doesn't change and can't be altered. This makes the warehouse a reliable source for analytics on past events, focusing on changes over time. You must store warehoused data securely, reliably, and in a way that's easy to retrieve and manage.
Maintaining a Data Warehouse
To maintain a data warehouse, you follow specific steps. First, there's data extraction, gathering large amounts from multiple sources. Then, the data goes through cleaning to fix errors.
After that, convert the cleaned data from database format to warehouse format. Store it, then sort, consolidate, and summarize for easier use. Over time, add more data as sources update.
Today, you can use cloud-based data warehouse services from companies like Microsoft, Google, Amazon, and Oracle.
Data Mining
Businesses warehouse data mainly for data mining, which means looking for patterns to improve processes. A good system lets departments access each other's data easily—for instance, marketing can check sales data to adjust campaigns.
The 5 Steps of Data Mining
- Collect data and load it into the warehouse.
- Store and manage the data on servers or in the cloud.
- Access and organize the data as business analysts, managers, or IT professionals.
- Sort the data using application software.
- Present the data in formats like graphs or tables for end-users.
Data Warehouse Architecture
Data warehouse architecture varies by needs, typically in one-, two-, or three-tier designs. Single-tier is rare, used for minimizing space in batch processing. Two-tier separates analytical and business processes for control. Three-tier has source, reconciled, and warehouse layers for long-life systems with extra review.
All architectures must meet separation, scalability, extensibility, security, and administrability.
Data Warehouse vs. Database
Don't confuse a data warehouse with a database. A database handles real-time updates with the latest data. A data warehouse aggregates structured historical data—for example, keeping all customer addresses over 10 years, not just the current one.
Data Warehouse vs. Data Lake
Both hold data, but a data lake stores raw data without a set purpose, used by data scientists. A data warehouse has refined, filtered data for specific uses, accessed by business professionals. Lakes are easier to update; warehouses are more structured and costly to change.
Data Warehouse vs. Data Mart
A data mart is a smaller data warehouse, collecting from few sources and focusing on one area. It's faster and easier for analysis in specific departments, acting as a subset for targeted reporting.
Pros and Cons
A data warehouse gives a competitive edge by tracking and analyzing pertinent information over time for informed decisions. It serves as a historical archive shareable across departments.
However, it drains resources and burdens staff with routine tasks. Building it takes time, human errors can hide for years, and multiple sources may cause inconsistencies.
Data Warehouse FAQs
What is a data warehouse used for? It's a storage system for historical data analyzed in various ways to gain insights and plan improvements.
For an example, consider a company expanding exercise equipment; it uses the warehouse to analyze customer data and retailer success for better decisions.
Stages of creation include setting objectives, collecting info, identifying processes, modeling data, locating sources, setting tracking, and implementing.
SQL is a language for databases, not a warehouse itself. ETL stands for extract, transform, load—combining data into the warehouse.
The Bottom Line
In essence, the data warehouse is your company's repository of business information over time, built from key department inputs, serving as the source for analysis that reveals past performance and guides decisions.
Other articles for you
Negotiation is a strategic discussion to reach mutually acceptable agreements through compromise.
The federal discount rate is the interest rate the Federal Reserve charges banks for borrowing funds, serving as a key monetary policy tool distinct from the federal funds rate.
NASAA is an association of North American securities regulators dedicated to protecting investors from fraud through education, enforcement, and regulation.
A trading desk is a specialized area in financial institutions where professionals buy and sell securities like equities, bonds, currencies, and commodities to facilitate market liquidity.
An unsponsored ADR is a type of American depositary receipt issued by a bank without the foreign company's involvement, trading over-the-counter and often lacking full shareholder rights.
The income effect describes how changes in a consumer's income or purchasing power influence their demand for goods and services.
A construction loan is a short-term financing option for building or renovating homes, often converting to a permanent mortgage upon completion.
Overweight in investing means allocating a higher-than-normal percentage of a portfolio to a specific asset, sector, or stock expected to perform well.
Noise in financial markets is misleading information or activity that obscures genuine trends, complicating investors' ability to assess true market movements.
A debenture is an unsecured debt instrument issued by corporations or governments, backed solely by the issuer's creditworthiness and reputation.