In the ongoing effort to properly collect and utilize data, operations can quickly become complex. This is especially so in the financial industry, where big data holds tremendous potential but also leads to common pitfalls. To effectively use big data, many financial institutions are turning to data warehouses, while others are reluctant to adopt the new technologies associated with them. This article intends to look at data warehousing, the important role it plays in gaining a competitive advantage, how it can benefit your organization, and some of the more common finance industry use cases.
What is Data Warehousing?
Data warehousing is essentially a type of technology which takes data from multiple diverse sources and places them inside a central repository for further use. Data warehousing may also refer to the very act of building and using a data warehouse.
A data warehouse basically stores a copy of the information an organization has gathered from their transaction systems and relational databases. People are able to access this vital information through a number of methods such as structured query language (SQL) clients, business intelligence tools, and applications designed for that purpose.
The architecture found in data warehouses includes a bottom tier where the database server is located. That’s how data is loaded and stored. The next tier up has the analytics engine, while the top tier is what users experience on the front-end as they see the results of their searches and analytics.
Financial data warehouses work similarly to a normal data warehouse. Once data is collected and deposited into a data warehouse, that data is then organized into specific schema that categorizes the information. This provides quick access to the data when it needs to be analyzed.
The Benefits of Using a Data Warehouse
Financial companies thrive through their data, so having a data warehouse is helpful for promoting growth. But there are more specific ways in which data warehouses can benefit financial services.
- Restructured Data
Data can get to be quite complex, especially when it comes to finances. One area where data warehouses shine is in restructuring data in such a way that it becomes more usable to regular business users. Many users may not be familiar with data science, SQL, and analytics, but data warehouses can make it so that the data is more understandable. In turn, the users will be able to utilize it for their financial business purposes.
- Improved Decision Making
Businesses base their decision making on data, so having better data on hand means better decision making practices. Data warehouses can help improve the quality of data, which means the data your financial organization will use is more accurate and consistent. And once your information is of a higher quality, your decisions based off of that data will be more accurate as well. At a time when financial predictions need to be precise, an enterprise data warehouse gives you that much needed advantage.
- Stored Data History
Data can change over time, so it’s helpful to have access to data at specific points in its history. After all, financial services like hedge funds need historical data in order to conduct audit trails and allow for backtesting. Data warehouses helps access that by maintaining that data history. This is especially useful if the source transaction systems don’t maintain it themselves.
- Easier Data Integration
Financial data can come from many different sources, so integrating them within a single source is particularly helpful. Data warehouses can help in this effort, making it much easier than before. It’s worth noting that this can also be done with alternative data, which is information that comes from sources outside of traditional ones. In the financial industry, some alternative data sources include satellite imagery, social media, email receipts, and web browsing behavior. The financial industry can benefit greatly from the use of alternative data, and data warehouses put those benefits within reach.
How the Financial Industry Uses Data Warehouses and Data Science
Now that you know some of the benefits of data warehouses, let’s look at how financial institutions are using them in conjunction with data science to gain an advantage.
- Analytic Types
Many companies are looking to use financial data in a variety of analytics pursuits. There are two areas of analytics most common in finances: predictive and real-time. Predictive analytics is all about discovering patterns in financial data to be prepared for future events. Real-time analytics is used in a number of different approaches like consumer insight, fraud detection, and more.
- Capturing Customer Data
Data science has allowed financial companies to be better at capturing and analyzing customer data. This is especially important considering the complexity of that type of data capture. Customers now use multiple channels on multiple devices, so collecting data on them has become more difficult and will likely continue to do so. Data warehouses give organizations the ability to capture every interaction with a customer, giving them unparalleled insight into what drives them.
To remain competitive, many financial organizations have sought to engage more with customers. One of the ways to do this is through more personalized messages, all made possible through the use of data science. The ability to craft more personalized interactions means engage with customers at the most opportune times with the most effective message.
- Risk Management
Perhaps the most common way in which financial companies use big data is through risk management. Risk can come from a variety of places — investors, competitors, and more — so managing that risk through enhanced machine learning algorithms becomes more important than ever. Automating that risk management also holds incredible potential, so financial institutions can be certain they remain on sure footing.
Web Data Integration Brings It All Together
Handling all this data can quickly become complicated, which is why it is often most helpful to have a single, unified platform to do it. That’s where Web Data Integration comes in. The data warehouse — the ability to store the data extracted for future reference — is just one component of the Web Data Integration lifecycle, which includes identifying what type of financial data to get, extracting it, cleaning it, and integrating it with a financial company’s existing business applications.
All of this is intended to properly analyze the data so businesses can use it for making important decisions regarding current and future strategies. Import.io provides you with a Web Data Integration platform that allows you to access financial data at a scale you’ll want. If you’d like to get that data now, you can sign up for a free seven day trial. Or you can talk to a data expert and discuss your data needs while learning more about how we can help.