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MongoDB database shines; customer data analysis brings challenges

A company's view of what data offers constantly evolves, whether it's seeking more unified customer data analysis on the front end or applying new technology to enterprise databases on the back end. This episode of BizApps Today explores both topics.

The video opens with a nod to the MongoDB database, which continues to draw attention in the NoSQL world. Open source database company MongoDB Inc. acquired a new storage engine earlier this year and promises new analytics benefits in an upcoming release. Those two aspects appeal to large enterprises using NoSQL, said Jack Vaughan, news and site editor for SearchDataManagement.

MongoDB has shed its early image as a hip tool for application development, thanks to its NoSQL product. "It's just not a Web thing or a hip thing," Vaughan told host Laura Aberle. "Big companies are seen using NoSQL software … For them it's just something more agile than SQL."

Changes to MongoDB database storage engine

In February 2015, MongoDB 3.0 database debuted to fanfare as the company swapped out an old data storage engine in favor of WiredTiger, which it owns through an earlier acquisition. Attendees at the recent MongoDB World 2015 conference applauded WiredTiger's features.

"The users at the conference told me as a default engine, it has a lot of value," Vaughan said. "It will enable more scalability."

Meanwhile, enterprises are watching for MongoDB 3.2's release later this year. The update will offer companies a new connector for BI and visualization efforts with NoSQL-based analytics.

Unifying customer channels through data analysis

MongoDB 3.2's upcoming release will offer companies a new connector for BI and visualization efforts.

BizApps Today also explores the growing concern of how companies can best attain a unified view of their customers despite often uneven data from various channels, such as mobile promotions and social media.

Lauren Horwitz, executive editor of SearchCRM and SearchContentManagement, traveled to The Social Shake-Up 2015 conference to learn more about the challenge of making customer data analysis more consistent and accurate.

"Experts counsel that companies need to start slow and … tackle one channel at a time in terms of matching up that data with other data silos and experimenting in terms of how they message customers in various channels," Horwitz said.

For example, at The Social Shake-Up event, representatives from The Home Depot talked about struggles with aggregating customer data, including how to pull information from specific channels, she said.

Let us know your thoughts on MongoDB databases and unified customer data analysis. Email news director Scott Wallask or follow him on Twitter: @Scott_HighTech.

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