New white paper released on optimizing marketing-related data in the data lake

Learn how businesses using data lakes can get the most out of survey data for more complete consumer insights.

We have just released a new paper, “Survey data, meet data lake. Data lake, meet survey data.” The paper outlines powerful ways for businesses to get the most out of marketing-related data stored in a data lake, including high-value primary research data. It dives into the unique complexities of this type of data and how to best handle them, so that businesses can focus on key goals, like innovation, customer service, and the development of products and services.

“We know that consumer insights are a vital data stream that many organizations are storing in their data lakes,” said Geoff Lowe of Infotools. “With our lessons learned and experience working with some of the world’s largest brands, we’ve come up with solutions that will help businesses use this data to their best advantage.” 

Businesses want to use their marketing-related data to help map customer journeys, understand motivations, and proactively develop products, services, and communications that will lead to organizational success. Shaping survey data properly, both on its way into and out of the data lake, is a critical part in building understanding about why consumers or customers are doing what they are doing, and informing ways to optimize their journey. 

“Survey data, meet data lake. Data lake, meet survey data” explores some vital themes such as:

  • Optimizing the technology stack used to import and access the information stored in data lakes or other cloud-storage repositories
  • Handling the complexities of survey data analysis and reporting, including weighting, multi-level responses, and data relationships and comparisons
  • Extracting the most value from the data stored in the data lake with solutions that work within a company’s existing environment, including complying with security protocols and processes.

The full paper can be downloaded here:

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