What is data warehouse

A data warehouse is a space where structured data is stored, analysed and fetched. The data can be historical data or new data. Small and medium-sized businesses don’t use data warehouses but use cloud-based services for storing data.

Big organizations and multinational companies use data warehouses for storing their large data.

Suppose a large company uses a data warehouse to store employee’s data. If the HR team of the company wants to increase the salary of employees then the HR team queries all employee’s data that is stored in the data warehouse. The data is stored in the form of a database. The database stores all information about the employees such as sales done by the employees, employee’s attendance, employee’s current salary etc. The HR team uses a data warehouse to increase the salary of employees.

Note that data warehouses don’t store unstructured data. A data warehouse first analyzes the unstructured or raw data and after filtering the data through software, it stores structured data.

Let’s now discuss some pros and cons of data warehouse.

Advantages of data warehouse

Some benefits of a data warehouse are:-

Quality of data:

The data is stored in ordered form. The data is transformed and cleaned through the software. The raw data is purified and the quality of data is improved.

Easy to access:

After the data is stored the fetching and retrieval of data becomes easy. Any person who has the knowledge to query the database can fetch the data easily.

Easy decision-making:

The executives of the company have all the information accessible through the data warehouse so they can make decisions accurately.

High response time:

The query of data through the database becomes fast. The servers which store data are high-speed. So fetching any type of data can take no time. The data is queried in a very fast way.

Follow rules:

The data is stored after following strict rules and privacy. All the privacy precautions are followed to store data. The system should work in private access and no outer person can have access to the data.

Competitor war:

The data of the company is stored in such detail that it can compete with the competitors. The profit and loss of the company can be easily noted through the data warehouse.

Save time:

The reports of the company can be retrieved easily and it saves a lot of time. It is not necessary that only the IT department of the company can fetch data but any skilled person can get data from the database.

Customer relationship:

The previous data of the customers are all stored in the data warehouse. This helps to have a good relationship with the customer. The company can give special discounts to the previous customers.

No duplicate data:

The data that is stored in the data warehouse remains consistent and duplicate data is not stored in the database. This is because all the data first goes through data cleaning software.

Optimized for large data:

Data warehouses are eligible to store large amounts of data. There is a large capacity in the data warehouse to store new data. The database in the data warehouse is updated daily without any space limitations.

Data mining:

The data in the data warehouse goes through data mining and hidden data is discovered through the data mining process. The hidden patterns to find data are used to recover and discover old data.

Intelligence used:

For going deep in the data analysis, business intelligence is used. Different tools are used to get data that is difficult to find in normal cases.

Auditing:

The auditing of a company becomes easy as all the records are saved in the data warehouse. All the customer, competitor and employee records are already present in the database so auditing becomes easy.

Advanced queries:

Data warehouse uses in-built techniques by which advanced queries can be eliminated by simple queries. The data is fetched in simple steps and there is no need to remember complex queries.

Disadvantage of data warehouse

Some drawbacks of a data warehouse are:-

Maintenance required:

It is required for a data warehouse to have maintenance costs. Additional staff is needed that can do the cleansing of data. Specialized software is also needed which can do maintenance of data.

Sometimes slow:

If the data warehouse is not accurately designed then it takes a large amount of time for queries. The data that needs to be retrieved is sometimes not ordered.

High-skilled professionals:

A person who can use and fetch data from the database is not enough for the data warehouse. It needs highly skilled professionals who can design the database for the data warehouse. There are multiple servers that need to be integrated with each other.

Extra servers needed:

If you want to store extra data that is not related to already stored data then you need extra servers. New data silos are needed to be added to the data warehouse for better company decisions.

Training needed:

It needs for all staff of the data warehouse to be fast trained. Data warehouses store a vast amount of data. If the staff of the data warehouse is not skilled then they can damage the stored data.

High cost:

Building a data warehouse is very expensive and small or medium-sized organisations cannot afford to build a data warehouse. The software, hardware and professionals are expensive for the data warehouse.

Resale value:

A data warehouse is not meant for a profit point of view. The return on investment of a data warehouse is not good. The purpose of a data warehouse is only for the use of the company.

Security problem:

There is a security problem in protecting the data. As all the data is stored in centralized servers, making secured data is difficult. It needs higher protection criteria to save the data from unauthorized personnel.

Changing business:

As all the structure of a data warehouse is dependent upon one specific business type. If the owner of the business changes his business so data warehouse should also be changed which costs higher expenses.

Data is real-time:

If data is updated in real time then fetching real-time is difficult. The real-time data needs to be processed before saving to the data warehouse.

Not for small business:

Small businesses cannot afford to use data warehouses because they need to buy high-priced servers. The servers need a cooling system which is also expensive.

Only structured data:

A data warehouse can only store structured data so it is not suitable for storing unstructured data. If a company has to store unstructured data, it needs to use different technology.

Dependent on one technology:

Once the company sets up the data warehouse then the company becomes dependent on it and it becomes difficult to change their mind to use other technology. It is very expensive to change the data warehouse structure later on.

Updating data:

To get the latest reports, the software needs extra time to process new data. When the new data comes in the data warehouse it needs to be filtered which is a time-consuming process.

Examples of data warehouse:

Some examples of data warehouses are:-

• Teradata
• Snowflake
• IBM Db2 Warehouse
• Amazon Redshift
• Actian Avalanche
• Oracle Exadata
• Google BigQuery
• Yellowbrick Data Warehouse
• Microsoft Azure Synapse Analytics
• SAP BW/4HANA