Small, local banks usually can’t compete with the likes of Bank of America or JPMorgan Chase when it comes to breadth of products, number of ATM locations, name recognition or market-moving power. In order to attract and retain customers, local banks must deliver high-quality, personalized customer service to each and every customer.

That’s the approach taken at Frost Bank, a San Antonio, Texas-based bank with $17 billion in assets (by comparison, Bank of America, the largest bank in the U.S., manages $2.2 trillion in assets). According to Frost, “Bankers should know their customers by name and vice-versa,” and “All the ATMs in the world are no substitute for customer service.”

Living up to that pledge, it turns out, requires a Big Data strategy. Frost Bank collects customer-related data from over 60 sources, including Salesforce.com and myriad internal and external databases. Previously, the bank used numerous data integration tools in conjunction. But with so much data coming at it from so many sources, the bank realized it needed to invest in a comprehensive data integration and data quality platform that would allow it to break down information silos and deliver a “single version of the truth” view of each customer.

The bank eventually decided on Informatica’s core platform, Informatica PowerCenter Advanced Edition, for the job. The platform includes data migration and data synchronization components, as well as a master data management module that identifies and removes inconsistencies and duplicates in customer data. Its Data Explorer module also helps enterprises identify relationships across customer records.

Since deploying the Informatica platform, Frost has reduced the average time of integration projects by nearly two-thirds. Most importantly, Frost’s sales team has access to timely, clean customer data. Not only do they know each customer by name, but the data also helps Frost sales associates identify potential cross-sell and upsell opportunities that align with each customer’s personal finance goals.

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While analytics capabilities and storage requirements get the lion’s share of attention when it comes to Big Data projects, data integration and data quality should not be overlooked. In order for enterprises and SMBs alike to provide top-notch customer service, they must have access to timely and accurate data. In some cases, homegrown integration tools are up to the task. But as companies start to run up against Big Data challenges, comprehensive platforms are needed in order to handle the volume, variety and velocity of data in question.