A data warehouse refers to the collection and management of data from multiple sources. It serves the purpose of offering a meaningful business insight. It is deployed for connecting and analyzing the data of business from different sources. The system forms the core of any business intelligence system created for data reporting and analysis. ‘
A data warehouse is a mix of components and technologies that promote the strategic deployment of data. It stores an extensive amount of data electronically for the business. It is created and designed for queries and data analysis instead of the processing of transactions. It refers to the process of transforming data into relevant information in time for making informed business decisions.
Note, the data warehouse is generally separately maintained from the operational database of the business. It refers to an environment moreover a product. It is an architectural build of a data system that gives the end-user current and historical data that is complex, hard to access, and present to users with the help of a database.
For instance, take the case of a 3NF database for any inventory system. It may have multiple tables connected. Like a report on the inventory information currently can have over 12 join conditions. This slows down response times of the report and the query. Whereas any data warehouse offers an innovative design that decreases this response time to help improve the query performance for analytics and reports.
Other names for a data warehouse
The following are some other names for the data warehouse-
- Executive information system
- Management information system
- Decision support system.’
- Business Intelligence System
- Analytical application or
- Data warehousing
Who should use a data warehouse?
The following businesses or users should use a data warehouse-
- Users or businesses who need to make decisions involving volumes of data
- Businesses looking for simple technologies to view data
- Those looking for systematic approaches for decision making
- Accelerating performance when it comes to the access of large volumes of data in the form of grids, charts, or reports.
- Helps in identifying hidden patterns of groups and data flows
How does the data warehouse function?
Experts from the USA’s esteemed company, RemoteDBA, state that a data warehouse functions like a core repository where the data comes from more than one source. This data goes into the data warehouse from relational databases and other transactional systems. This data can be-
- Semi-structured or
The above data is later processed, changed, and stored in such a manner that users can easily access this processed information in the data warehouse via BI tools, spreadsheets, and SQL clients. The data warehouse can combine all the information arriving from different data sources to place them in a single extensive system.
When this information is merged in a single platform, it can quickly analyze all its customers holistically and straightforwardly. This allows the business to get all the information it needs. It makes the process of data mining possible. This means hidden patterns in the obtained data can easily be obtained, and this leads to better sales and profits with success for the business.
What are the 3 types of data warehouses?
The following are the 3 types of data warehouses-
1- Enterprise Data Warehousing – This is a centralized repository of information. It offers support services for decision making across the total enterprise. It gives the unit a single unified approach for the organization and the representation of data. It provides the enterprise with the ability to divide and classify the data as per the subject. Based on this classification, it allows access to these divisions.
2- Operational data stores – This is often referred to as ODS and is excellent for businesses where OLTP systems and data warehousing are not supported for their reporting needs. Real-time refreshments of data can be obtained in this system, and it is ideal for any routine task like storing Employee records of an organization.
3- Data Mart – This refers to any subset of the data warehouse. It is created and made for a specific line of businesses like finance, sales, and the like. In this type of data warehouse, the information or the data can easily be collected from the source.
Embrace the best practices for a data warehouse
- Work on a plan for testing the accuracy, consistency, and integrity of the collection of data
- Make sure that your data warehouse is well defined, integrated, and time-stamped.
- Ensure you embrace the correct tool, arrest data conflicts, confirm to life cycle requirements and learn from all the mistakes you make
- Reports and operational systems should never be replaced.
- Do not waste time on data extraction, loading, and cleaning.
- Involve all your stakeholders and business personnel in the implementation process of data warehousing. Note, any data warehouse should be a team project. You should not create data that is not useful to users.
- Make sure you prepare a good quality training plan for all your end-users.
- Data warehouse permits the end-user to access critical data quickly from different sources on one platform
- Get consistent information on various cross-functional tasks. Get support for ad-hoc reporting and queries.
- Complete integration of several sources of information to decrease stress on production systems
- Reduce the TAT for reporting and analysis
- Easy integration and restructuring for reports and analysis
- Faster retrieval of data
- Historical data in a single place helps you analyze trends and periods from different times to predict future analysis.
- Not great for unstructured data
- Creation and implementation become a time -consuming affair
- Gets outdated quickly
- Challenging for changes in indexes, queries, data types and more
- Users must have required training to use a data warehouse.
A data warehouse is excellent for the analysis of a business; however, when you embrace it, make sure you have well-trained experts to take care of it well. It is your central repository of core information essential for detecting hidden patterns and informed decisions.