Data Warehousing in Banking Industries

In general, data warehousing is a house of data, a place where data is stored centrally, that provides report and data analysis. Data Warehousing is a process of collecting and managing data gathered from various sources to provide meaningful business insights.

A Data warehouse is naturally used to connect and analyze business data from diverse sources. A data warehouse is the mainframe of Business Intelligence systems which are built for analyzing and reporting data. It also comprises of the blending of technologies and components which aids the strategic use of data

Data warehousing is also known for its electronic storage of a large amount of information by a business or organization which is designed for query and analysis instead of transaction processing.

Enterprise Data Warehouse (EDW)

This is a centralized type of warehouse that provides decision support service across the enterprise and offers an incorporated approach for organizing and representing data. Also, it provides the ability to categorize data according to the subject and give access according to those divisions.

Operational Data Store

Operational Data Store, also known as ODS is a type of database that provides a snapshot of the up-to-date data from several transactional systems for operational reporting. It also allows organizations to associate data in its original format taken from various sources into a unified
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Operational Data Store, also known as ODS is a type of database that provides a snapshot of the up-to-date data from several transactional systems for operational reporting. It also allows organizations to associate data in its original format taken from various sources into a unified destination to make it available for business reporting. In the Operational Data Store, the data warehouse is restored in real-time. Because of this, it’s now widely preferred for routine activities like storing records of the Employees.
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Data Mart

A data mart is a sample of the data warehouse, that is specially designed for a specific line of business, such as sales, finance, sales or finance. Data marts are often made and controlled by a single department in an organization.

In Banking, for example, there are many systems in which we can use data warehousing for example; ATM systems, Financial systems, Accounting systems, card systems etc.

A data warehouse is like a centralized body where information is brought from multiple data sources, wherein the data flow into a data warehouse from the transactional system and other relational databases.

The data is divided into three parts:

• Structure

• Semi-Structured

• Unstructured data.

For more data and more problems

Big banks and banking organizations face this problem of having more data which leads to more problems.

Although banks use different applications and have various systems in place. But what if all financial data was kept in just one system, it would be much faster to gather and analyze data. But it’s not that simple.

Starting banks/business companies, they have core banking systems, that drives daily activities like deposits, withdrawals, and loans and over the years, banks have adopted more technology. We now have online banking, as well as software for mortgages, treasuries, and investments.

Trying to understand data across multiple systems can be a big challenge especially when you know how big and complex banking data is.

A typical banking professional would not understand the databases, for instance, housing the data and the calculations that are necessary to extract and transform data. With the way data is growing exponentially, and spreading across systems it’s more important now than ever to bring it together in one spot.

In this case, banking professionals use data warehousing as a centralized body to simplify, analyze and standardize the way data is collected. This makes it easy to process and access data instead of having multiple Application.

To Keep Data Secured

"There’s a big difference between providing useful banking data and risking the security of that data. In the absence of a data warehouse, it’s easy to accidentally compromise valuable data. By having a data warehouse, you can store data securely locked up and still provide useful information to those who need"

Banks are now opting to implement a data warehouse because it generates a copy of the data. Wherein you can provide that copy to any banking professional for analysis while holding to the original dataset.

To Measure Success and Account for Failures

Another reason why banking organizations need data warehousing is to know the progress of the organization.

Where they are succeeding or not and in which areas they should improve.

As the world is improving there are trending issues to consider in real-time, like what’s happening with customer deposits? How about loans? Is your bank meeting the reserve requirement?

By considering trends over time, you need historical data. And the problem with historical banking data is that it can be difficult to get. It’s scattered everywhere in every system, but it might be archived or difficult to access for reporting.

Providing a report on all banking data both present and historical requires a data warehouse. Wherein you can access and merge real-time and historical data to various systems and provide it to anyone in need of it.

A lot of banking industries are adapting data warehousing in solving data management issues and reporting problems and improving Banking industries. Do you think data warehousing is worth trying or not? Kindly let us know in the comment section below.