In today’s fast-moving technology environment, the most important aspect is the data or information which forms the backbone for any organization. Database and Data Warehouse are two commonly used systems for managing data. Although both of them perform the same task of data administration, there is a spring difference between these two concepts as they serve different purposes and utilize different technologies in the management of data.
Database vs Data Warehouse
The difference between Database and Data Warehouse is that Database is used to record data or information, while Data Warehouse is used mainly for data analysis.
However, the above is not the only difference. A comparison between both the terms on certain parameters can shed light on subtle aspects:
Comparison Table Between Database and Data Warehouse (in Tabular Form)
|Parameter of Comparison||Database||Data Warehouse|
|Meaning||An organized collection of data stored and accessed electronically||System used for storing, retrieving, managing, reporting and analyzing large amounts of any type of data|
|For what purpose?||For storing of data||For analysis of data|
|Procedure used||Data is captured/populated||Data is scrutinized/analyzed|
|Processing method||Online Transactional Processing||Online Analytical Processing|
|Techniques/methods||ER modeling procedures||Data modeling procedures|
|Storing data||Flat Relational Approach technique||Dimensional, snowflake method|
|Decision making||Not much used as it only involves storing of data||Highly useful as it analyses the data|
|Where is it commonly used?||Used in almost all industries, such as banking, finance, healthcare, telecommunication, aviation, however, usage will be limited to storing data, customer records, bills, stock and sales information||Used in almost all industries, such as banking, finance, telecommunication, aviation, however, usage will be for analysis of information, predicting outcomes, studying patterns or behaviors, and helping in overall decision making.|
What is Database?
Database is usually a huge collection of data systematically organized into columns and rows. In other words, Database can be considered as a collection of pieces of information that is organized and used on a computer/system. Database is the foundation or the starting phase of the building or analysis of data.
Database will usually contain data or information which is organized in columns, rows, and tables. The data can be periodically updated or indexed as necessary to make it easily accessible or being retrieved. Organizations utilize Database management systems (DBMS) for storing customer, inventory, finance, sales, or human resources information.
Database offers multiple advantages such as easy search and retrieval, security features, sharing of data, multiple views, supports multi-user framework, and multi-transaction processing. Most importantly, Database follows the ACID compliance (Atomicity, Consistency, Isolation, and Durability) model which avoids duplicate processing and other errors.
Database is not free from the cons. Some of the features of a Database that make it not a worthwhile option for many include the cost of implementation which is quite high for large amounts of data, the complexity of some Databases which again increases the cost in understanding and training, and problems with compatibility with other systems.
Database may not be able to undertake complex operations/calculations and analysis of data and hence decisions cannot be taken based on the data stored in the Database.
What is Data Warehouse?
Data Warehouse is a system or method used for analyzing and managing huge amounts of data. Data Warehouse can be considered as an information or documentation set up to store and analyze complex and large volumes of historical and current data.
Data Warehouse garners data from multiple sources, analyses the same and helps in generating reports for management purposes. The data to be analyzed can be from a single or multiple applications or sources. Data Warehouse uses complex queries to generate customized analytical reports.
Data Warehouse is primarily used for reporting, condensing, analyzing, and integrating data for decision-making purposes. Data Warehouse includes advanced methodologies to enable quick search, advanced filters and accurate analysis. Data Warehouse can be considered as a single version of truth (SVOT) for an organization regarding analysis and decision making. Data stored in a Data Warehouse is non-volatile, meaning it will not be erased when new data is being added.
Data Warehouse is not free from shortcomings. Some of the common problems of Data Warehouse include high costs associated with implementation, maintenance, and training as it is complicated. Data Warehouse involves too much time consuming for certain activities such as loading, and extracting the data, adding new data, or updating existing data.
Main Differences Between Database and Data Warehouse
- A database is utilized for data storage. Data Warehouse is utilized for data scrutinizing and analysis.
- Database utilizes the Online Transactional Processing (OLTP) method for storing data. Data Warehouse utilizes the Online Analytical Processing (OAP) method for analysis of data.
- Database is commonly used in performing operational aspects of business. Data Warehouse touches on the deeper aspects of business i.e. analyzing the data for decision making.
- Database usage may be restricted to only a single application. Data Warehouse usage can involve multiple applications.
- Database will use simple query types. Data Warehouse involves complex queries due to the analysis requirements.
- Database will commonly have data which is always new. Data Warehouse may not always have up to date data.
Database and Data Warehouse are distinguishable in their data management abilities. Both offer multiple but distinct sets of benefits and come with certain cons. Database will assist in the basic business operations while Data Warehouse will be instrumental in interpreting data for decision purposes. Therefore, it is important to assess these aspects and also the individual/organizational/divisional needs before deciding to adopt either of Database or Data Warehouse.
A prudent option would be to start with Database and later move to Data Warehouse or in the alternative implement not too complex systems in the initial phase of data management especially if the data involved is not too large or complex.
A thorough practical understanding and advice especially from data management specialists is suggested to reap the full benefits of either the Database or Data Warehouse deployment. The most important focal point which should always be kept in the perspective is whether the implemented system will serve the ultimate purpose of the organization.
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