Data is an essential core component of every function. From marketing to forecasting, data provides immense value to both consumers and producers. Understanding data and how it works is crucial to sustaining businesses. To understand data, it is essential to understand data warehousing. This article outlines what data is and what does data warehousing allow organizations to achieve.
What is Data Warehousing?
Data warehousing is the epitome of data consolidation. It contains tons of valuable data that companies can use to improve their operations. A data warehouse can be defined as a data management system that contains historical data extracted from various sources.
IBM researchers Barry Devlin and Paul Murphy introduced the concept of data warehousing in 1988. By the end of the 20th century, many businesses started to rely on computers to store their important data. Hence, the concept of data warehousing came into being.
What Does Data Warehousing Allow Organizations To Achieve?
Data warehousing is vital for businesses. It offers data analysis and allows companies to gain insights into the future. By analyzing data, they can forecast future trends and how they can sustain their business operations. Data scientists can use this data to analyze businesses and allow them to improve their decision-making.
In simple words, a data warehouse simplifies business operations and saves time. The different departments within a company have tons of data that are stored in their respective systems. Extracting data from such systems can be time-consuming. A data warehouse stores data from all departmental systems into a single platform. Thus, it makes it easier for people to extract relevant data within seconds.
Objectives of Data Warehouse
Let’s discuss how and what does data warehousing allow organizations to achieve.
- Utilizes advanced data storing technology that is highly scalable and manageable.
- Stores data as structured and unstructured data.
- Gathers data and stores it in a uniform format to provide ease to data scientists.
- Ensures stability of the data.
- Allows businesses to make better and more timely decisions.
Elements of Data Warehouse
A typical data warehouse comprises the following elements.
- Contains a relational database that manages and stores data.
- An Extraction, Loading, and Transformation (ELT) solution prepares the data for analysis.
- Constitutes analysis and data mining techniques.
- Client analysis tools for visualizing and data presentation.
- Advanced technologies and computer vision software algorithms allow extensive data analysis.
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Advantages and Disadvantages of Data Warehouse
A data warehouse has a litany of benefits for the company, such as
- It gives a company a competitive edge by allowing it to retrieve historical data and make informed decisions.
- It maintains and organizes important company data.
- It automatically backs up the company’s data, so the chances of data getting lost are the bare minimum.
Disadvantages of Data Warehouse
While a data warehouse has many benefits, there are certain downsides to it too
- It is a bit costly as the company needs to constantly maintain it.
- It requires more human labor to update the data warehouse.
- If an employee mistakenly adds incorrect information to the database, it takes a lot of time to make amendments to it.
Types of Data Warehouses
The major types of data warehouses are:
Enterprise Data Warehouse
An enterprise data warehouse (EDW) is a central database of an organization that facilitates decision-making. It helps disseminate crucial cross-departmental information and helps people within a company make a timely decisions to avoid risk.
Operational Data Store
An operational data store (ODS) is a data warehouse that stores routine business information such as employee records. People can extract day-to-day data from ODS to perform any business operation.
Data Mart
A data mart (DM) is a type of data warehouse that stores data of a particular department. There are multiple departments within an organization, such as marketing, finance, HR, etc.
Each department has its own data mart. The marketing departments’ data mart contains information regarding sales, customer data, and key marketing insights. The enterprise data warehouse takes data from the data mart and stores it in an operational data store daily. The concerned persons can then extract information as they like.
What Does Data Warehousing Allow Organizations To Achieve In Different Sectors?
Some of the examples of data warehousing are:
Retail Sector
Data warehouses in retail industries help store marketing data such as customer reports, pricing policies, promotional deals, customer buying behavior, number of sales made, etc. It also allows companies to do forecasting based on their current sales.
Healthcare Sector
In the healthcare sector, a data warehouse can store patients’ data such as treatment reports, appointment details, medicine reports, and relevant data to transfer to concerned healthcare departments.
Conclusion
In a nutshell, data warehousing is quite essential for companies regardless of sector. It saves time, performs instant business information processing, and allows companies to generate immense revenue.
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