A database is a collection of related data which represents some elements of the real world. It is designed to be built and populated with data for a specific task. It is also a building block of your data solution.
In this tutorial, you will learn
- What is Database?
- What is a Data Warehouse?
- Why use a Database?
- Why Use Data Warehouse?
- Characteristics of Database
- Characteristics of Data Warehouse
- Difference between Database and Data Warehouse
- Applications of Database
- Applications of Data Warehousing
- Disadvantages of Database
- Disadvantages of Data Warehouse
A data warehouse is an information system which stores historical and commutative data from single or multiple sources. It is designed to analyze, report, integrate transaction data from different sources.
Data Warehouse eases the analysis and reporting process of an organization. It is also a single version of truth for the organization for decision making and forecasting process.
Here, are prime reasons for using Database system:
- It offers the security of data and its access
- A database offers a variety of techniques to store and retrieve data.
- Database act as an efficient handler to balance the requirement of multiple applications using the same data
- A DBMS offers integrity constraints to get a high level of protection to prevent access to prohibited data.
- A database allows you to access concurrent data in such a way that only a single user can access the same data at a time.
Here, are Important reasons for using Data Warehouse:
- Data warehouse helps business users to access critical data from some sources all in one place.
- It provides consistent information on various cross-functional activities
- Helps you to integrate many sources of data to reduce stress on the production system.
- Data warehouse helps you to reduce TAT (total turnaround time) for analysis and reporting.
- Data warehouse helps users to access critical data from different sources in a single place so, it saves user's time of retrieving data information from multiple sources. You can also access data from the cloud easily.
- Data warehouse allows you to stores a large amount of historical data to analyze different periods and trends to make future predictions.
- Enhances the value of operational business applications and customer relationship management systems
- Separates analytics processing from transactional databases, improving the performance of both systems
- Stakeholders and users may be overestimating the quality of data in the source systems. Data warehouse provides more accurate reports.
- Offers security and removes redundancy
- Allow multiple views of the data
- Database system follows the ACID compliance ( Atomicity, Consistency, Isolation, and Durability).
- Allows insulation between programs and data
- Sharing of data and multiuser transaction processing
- Relational Database support multi-user environment
- A data warehouse is subject oriented as it offers information related to theme instead of companies' ongoing operations.
- The data also needs to be stored in the Datawarehouse in common and unanimously acceptable manner.
- The time horizon for the data warehouse is relatively extensive compared with other operational systems.
- A data warehouse is non-volatile which means the previous data is not erased when new information is entered in it.
|Purpose||Is designed to record||Is designed to analyze|
|Processing Method||The database uses the Online Transactional Processing (OLTP)||Data warehouse uses Online Analytical Processing (OLAP).|
|Usage||The database helps to perform fundamental operations for your business||Data warehouse allows you to analyze your business.|
|Tables and Joins||Tables and joins of a database are complex as they are normalized.||Table and joins are simple in a data warehouse because they are denormalized.|
|Orientation||Is an application-oriented collection of data||It is a subject-oriented collection of data|
|Storage limit||Generally limited to a single application||Stores data from any number of applications|
|Availability||Data is available real-time||Data is refreshed from source systems as and when needed|
|Usage||ER modeling techniques are used for designing.||Data modeling techniques are used for designing.|
|Technique||Capture data||Analyze data|
|Data Type||Data stored in the Database is up to date.||Current and Historical Data is stored in Data Warehouse. May not be up to date.|
|Storage of data||Flat Relational Approach method is used for data storage.||Data Ware House uses dimensional and normalized approach for the data structure. Example: Star and snowflake schema.|
|Query Type||Simple transaction queries are used.||Complex queries are used for analysis purpose.|
|Data Summary||Detailed Data is stored in a database.||It stores highly summarized data.|
|Banking||Use in the banking sector for customer information, account-related activities, payments, deposits, loans, credit cards, etc.|
|Airlines||Use for reservations and schedule information.|
|Universities||To store student information, course registrations, colleges, and results.|
|Telecommunication||It helps to store call records, monthly bills, balance maintenance, etc.|
|Finance||Helps you to store information related stock, sales, and purchases of stocks and bonds.|
|Sales & Production||Use for storing customer, product and sales details.|
|Manufacturing||It is used for the data management of the supply chain and for tracking production of items, inventories status.|
|HR Management||Detail about employee's salaries, deduction, generation of paychecks, etc.|
|Airline||It is used for airline system management operations like crew assignment, analyzes of route, frequent flyer program discount schemes for passenger, etc.|
|Banking||It is used in the banking sector to manage the resources available on the desk effectively.|
|Healthcare sector||Data warehouse used to strategize and predict outcomes, create patient's treatment reports, etc. Advanced machine learning, big data enable datawarehouse systems can predict ailments.|
|Insurance sector||Data warehouses are widely used to analyze data patterns, customer trends, and to track market movements quickly.|
|Retain chain||It helps you to track items, identify the buying pattern of the customer, promotions and also used for determining pricing policy.|
|Telecommunication||In this sector, data warehouse used for product promotions, sales decisions and to make distribution decisions.|
- Cost of Hardware and Software of an implementing Database system is high which can increase the budget of your organization.
- Many DBMS systems are often complex systems, so the training for users to use the DBMS is required.
- DBMS can't perform sophisticated calculations
- Issues regarding compatibility with systems which is already in place
- Data owners may lose control over their data, raising security, ownership, and privacy issues.
- Adding new data sources takes time, and it is associated with high cost.
- Sometimes problems associated with the data warehouse may be undetected for many years.
- Data warehouses are high maintenance systems. Extracting, loading, and cleaning data could be time-consuming.
- The data warehouse may look simple, but actually, it is too complicated for the average users. You need to provide training to end-users, who end up not using the data mining and warehouse.
- Despite best efforts at project management, the scope of data warehousing will always increase.
What Works Best for You?
To sum up, we can say that the database helps to perform the fundamental operation of business while the data warehouse helps you to analyze your business. You choose either one of them based on your business goals.
- Database is a collection of related data that represents some elements of the real world whereas Data warehouse is an information system that stores historical and commutative data from single or multiple sources.
- Database is designed to record data whereas the Data warehouse is designed to analyze data.
- Database is application-oriented-collection of data whereas Data Warehouse is the subject-oriented collection of data.
- Database uses Online Transactional Processing (OLTP) whereas Data warehouse uses Online Analytical Processing (OLAP).
- Database tables and joins are complicated because they are normalized whereas Data Warehouse tables and joins are easy because they are denormalized.
- ER modeling techniques are used for designing Database whereas data modeling techniques are used for designing Data Warehouse.