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Why We Built a Marketing Data Lake

Why We Built a Marketing Data Lake

April 20, 2017 0 Comments
Marketing Data Lake
Find out how a data geek turned marketer built a data lake across many different systems, along with the good and not-so-good results.

As a geek turned marketer, my goal is to provide high-value technical content to my fellow data geeks. To better understand them, we started with our corporate data warehouse (EDW) and data management platform (DMP), but it was missing a lot of detailed data.

In addition to that, insights are fragmented across many different systems. Just thinking about a schema and the right questions to ask made my head spin.

So we decided to build a data lake for more flexibility in asking any questions with an ad hoc schema or read approach, against any customer data sets to better understand what our audience wants to consume. We also wanted a foundation for new and advanced analytics techniques against data sets we have yet to derive value from.

Progress Marketing Data Lake

Check out this article to find out how I did it, along with all the good and not-so-good results, including some of the things we’re now able to analyze, such as best target audience, lead routing effectiveness and popular data connectivity scenarios.

Invited to Present On Stage at Oracle Modern Customer Experience

If you’re going to Oracle’s Modern Customer Experience event on April 26 in Las Vegas, don’t miss my presentation on this same topic: Journey to Marketing Data Lake.

I’ll be discussing how we leveraged standard SQL (JDBC) and REST (OData) interfaces for simple, secure access to cloud marketing data for the data lake, such as Salesforce, Oracle Service Cloud, Eloqua, Marketo and Google Analytics.

READ THE FULL ARTICLE

Sumit Sakar

Sumit Sarkar

Sumit Sarkar is a Chief Data Evangelist at Progress, with over 10 years experience working in the data connectivity field. The world's leading consultant on open data standards connectivity with cloud data, Sumit's interests include performance tuning of the data access layer for which he has developed a patent pending technology for its analysis; business intelligence and data warehousing for SaaS platforms; and data connectivity for aPaaS environments, with a focus on standards such as ODBC, JDBC, ADO.NET and ODATA. He is an IBM Certified Consultant for IBM Cognos Business Intelligence and TDWI member. He has presented sessions on data connectivity at various conferences including Dreamforce, Oracle OpenWorld, Strata Hadoop, MongoDB World and SAP Analytics and Business Objects Conference, among many others. 

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