Data Management Use Cases at Nasdaq, Bausch & Lomb, Dallant, Financial Fabric, and Arabesque

Comprehensive data management is critical for companies to pull insights from their data.

Data analytics and business intelligence (BI) hinge on creative data management practices, which are also proven to increase operational efficiency and savings, according to vendor case studies.

See below how organizations today are working with vendors on their data management solutions:

Finance: Nasdaq

Nasdaq is a global financial services company that operates the Nasdaq stock exchange in the U.S. and eight European stock exchanges. 

The number of automated trading platforms has increased significantly, and since 2018, market volatility has also increased. 

To accommodate the large volume of transactions, a robust data management framework must be in place. Nasdaq switched to an Amazon Web Services (AWS) data warehouse to help them cope with the billions of records that they have to process daily. Nasdaq also implemented a data lake framework that allowed them to rapidly scale up when necessary. This is due to the ability of this framework to separate storage and computing functions. 

With this system in place, when market volatility spiked in February 2020 due to the COVID-19 pandemic, they were able to cope with the increased demand, which reached up to about 70 billion records daily, with a peak of 113 billion records. 

Processing these records quickly is essential for Nasdaq, as they rely on this for their billing and reporting processes. With their AWS solution in place, Nasdaq is able to finish loading the data necessary to generate their billing and invoicing information an hour or two after ther market closes.

Medical: Bausch & Lomb

Bausch & Lomb India is seeking to increase the amount of contact lens sales they make in the Indian market. 

However, in embarking on this campaign, they realized that moving through the various steps of offering free trials to facilitating purchases was a complicated process. 

To help with this, they enlisted the help of three Oracle products. They used Oracle Responsys Campaign Management to help run its marketing campaigns. This allows them to gather customer data efficiently and have it all in one place. With the platform, they were able to increase engagement and achieve higher conversion rates, while reducing the cost of acquiring customers. 

They also used the Oracle CX platform to help with the increased engagement and higher conversion rates. Finally, Bausch & Lamb made use of the Oracle B2B Service to manage customer and influencer data. This allows them to collect information that helps them to create personalized, automated communications that are useful for growing their market influence. 

With these products, they now have a detailed view of customer behaviors, and can see how customers interact with them and create more targeted marketing efforts.

Food: Dallant

As Dallant grew, they found it difficult to keep up with the demands of their client base. 

They needed a flexible support system, and they also needed an integrated, company-wide information management system. 

With SAP/4HANA, they were able to get a solution that helped them to increase administrative efficiency and overall productivity. 

One of the most significant benefits is the real-time oversight provided to them by SAP/4HANA. This allows them to make better data management and business decisions overall.

Finance: Financial Fabric

Financial Fabric recognized that to meet the needs of their clients that they needed a robust solution that allows clients to take advantage of analytics, while protecting confidential information. 

An in-house solution would have been cost-prohibitive, but they still needed a robust solution. They chose to use DataHub on Microsoft Azure, since it allowed them to achieve their goals, while maintaining a high level of security. Datahub takes in information to a data warehouse from a number of sources, such as fund administrators and prime brokers. This data is then used by business intelligence tools connected to Microsoft SQL Server Analysis services. 

Without this solution, analysts would have to manually gather and process data. Clients are able to generate high-quality analytics and reports with the data gathered without the need of specialized help.

Finance: Arabesque

Arabesque uses artificial intelligence (AI) to find general trends in markets that help its clients to create custom investment strategies. 

Instead of having their own infrastructure, they are using Google Cloud to help them to scale up their product. Before switching to Google Cloud, the company’s development team was spending time on DevOps activities that could have been spent on AI research, which is Arabesque’s core competency. 

They use a number of Google Cloud solutions in conjunction with Kubernetes to gather and analyze data on thousands of companies across 75 countries. 

By using Google Cloud, Arabesque allows their developers to focus on core business activities, it reduces the amount of training time for new developers, it allowed them to increase their market reach, and it also reduced their server costs, since Google Cloud operates on a pay-as-you-go model.