Cassandra

Econsultancy Google hangout: big data and best practices in data management – Thursday, December 13

Data has become such a popular topic in digital marketing circles that we’re running out of metaphors. But whether you think of data as the oil of marketing, a firehose of numbers or the next gold rush, chances are that your organization is still coming to grips with the possibilities and realities of “Big Data.”

As a great end of the year Google Hangout, join us December 13, 2012 at 12:30 EST as we discuss cutting-edge data techniques for supercharging advertising used by global corporations for marketing as released in the latest Econsultancy report “Best Practices in Data Management.” Data Management Platforms (DMPs) and Audience Management Platforms (AMPs) are all the rage, but getting the most out of data for audience segmentation, insights, and targeting takes more than just a relationship with a vendor.

What is a data scientist and do you need one?

Although it’s fast becoming a hot position, ask different people what a “data scientist” is and you’ll get different responses. Invariably, you’ll hear buzzwords like Big Data, Hadoop and Cassandra, as well as technical terms like predictive modeling and regression analysis.

If you’re not familiar with these, the role may be something of a mystery, but it is an important and lucrative one at many tech companies.

Best practices in data management: report

Data is everywhere. As the cost of storing and collecting data decreases, more of it becomes available to marketers looking to optimize the way they acquire new customers and activate existing ones.

In the right hands, data can be the key to understanding audiences, developing the right marketing messages, optimizing campaigns, and creating long-term customers. In the wrong hands, data can contribute to distraction, poor decision-making, and customer alienation.

Over the past several weeks, I asked over thirty of the world’s leading digital data practitioners what marketers should be thinking about when it comes to developing a data management strategy.

The result is the newly available Best Practices in Data Management report. A few big themes emerged from my research, which I thought I would share.

Five legitimate use cases for NoSQL databases

NoSQL may be one of the most overhyped technology trends in the past couple of years, and a growing number of companies that left their relational databases behind for a NoSQL fling are rethinking their decisions.

Yet organizations continue to adopt NoSQL solutions and investors are still eager to pour money into vendors behind the most popular of them.

Are they crazy, or has some of the NoSQL skepticism been overdone?

The truth of the matter is that, hype aside, there is a role for NoSQL solutions to play in a world consumed by data, and increasingly companies are making smart decisions about when to use relational databases and when to turn to their NoSQL cousins.

Has NoSQL been overhyped?

One of the biggest technology buzzwords to emerge in the past several years is ‘NoSQL.‘ Put simply, NoSQL has come to refer to any database management system that isn’t a traditional RDBMB.

From Cassandra to CouchDB, there are a number of NoSQL systems that have attracted significant attention, and that are used in commercial applications, including some of the most popular consumer internet services.

But the honeymoon with NoSQL may be coming to an end.