Data Warehousing Application in the Finance Industry

Decoding the core data challenges the finance industry businesses face and providing suitable custom warehousing solution
Data Warehousing Application In The Finance Industry - QuellSoft

Data processing and management becomes a huge concern for entities managing large amounts of data. Along with managing data across various sources and keeping the data accurate, they also need to keep in mind what it all is for, extracting valuable information from the data to improve in their processes.

In this case study, we talk about data warehousing solutions we provided to one of our clients in the finance industry. The client’s identity and other sensitive information will not be mentioned here for obvious reasons, but we address all the major challenges the client was facing and what data warehousing solutions we provided to them.

Challenge – Data Fragmentation and Inefficiency

One of the many challenges entities with large amounts of data face is data fragmentation. This was the biggest challenge our client was facing. Let us talk about it.

Nowadays, businesses have many data sources that they rely on for data, such as multiple tools like accounting software, ERPs, platforms like social media, websites, legacy systems, etc. This is here if not taken care of properly, data fragmentation can be harmful and prevent you from making the best business decisions.

It becomes a serious problem when businesses do not have a means of breaking down data silos and analyzing data to make decisions.

Data fragmentation also affects the quality of your data. The quality of your data is gauged by its accuracy, completeness, accessibility and consistency, all of which take a hit due to data fragmentation.

Moreover, data fragmentation can lead to noncompliance of regulations. If your data is scattered across platforms or databases, it can raise huge privacy concerns and can lead to lawsuits.

Hence, Data Fragmentation is not something to sleep on. Now, let us talk about the solution.

Solution – Data Centralization and Governance

We provided data centralization and governance through our data warehousing services to ensure that all the pain points in this challenge were addressed and remedied.

We provided a solution that centralized all the data in a single data warehouse. This methodology provides a centralized solution to all data across all various sources mentioned above and more, which helps businesses conveniently access and analyze their data to make decisions accordingly.

It also ensures quality of data, i.e., accuracy, completeness, accessibility and consistency, and regulation compliance.

Challenge – Unorganized Historical Data

Historical data is something that many businesses take for granted. When in reality, an organization’s historical data works as a treasure trove when utilized properly (as the old saying goes, old is gold). Look at it this way, your historical data tells you all about all your business decisions till now and how all your strategies have performed.

Our client was facing the same challenge. Their historical data was unorganized and scattered across various sources and legacy systems. For that reason, they were unable to analyze historical data and make informed decisions.

Solution – Data Integration from Legacy Systems to Data Warehouse

To address the client’s challenges regarding historical data, we provided a data warehousing solution that we call ETL (Extract, Transform, Load). Utilizing ETL, we integrated all their historical data scattered across various legacy systems and sources into a centralized warehouse, which allowed them to access all their historical data in a single warehouse and conveniently accessible format, ultimately allowing them to analyze the historical data efficiently and make informed business decisions.

Challenge – Ineffective Business Intelligence

Data is collected in large amounts from various sources to improve strategic decision-making by analyzing the data. That is called Business Intelligence. Challenges like data fragmentation and unorganized/inaccessible historical data make it impossible to make the best strategic decisions, in other words, ineffective business intelligence.

Solution – Data Warehousing

To speak in general terms, data warehousing is the ultimate solution for all challenges related to data analysis and strategic decision-making.

In this case study we talked about the major challenges our client in the financial industry was facing, how the challenges were affecting their business intelligence and how we provided the appropriate data warehousing solutions.

To conclude, data warehousing was the ultimate solution for our client’s improved business intelligence. If you are interested in knowing more about how data warehousing can help your business overcome its challenges, do not hesitate to reach out to us. We will be glad to help you.