Big Data Technology in Digital Marketing: Choosing a Stack That Works for You
It’s no small secret that digital data presents clear and present challenges for marketing organizations.
As consumers spread their attention across a wide variety of channels and devices, key sources of digital data such as websites, online ads and mobile apps, spin off massive amounts of data. This is the gold that all marketers seek to mine, refine and use to drive up the bottom line.
However, it’s one thing to know where the gold is. It’s an entirely different beast to actually get at it and use it to your advantage.
Like miners digging through a mountainside using highly specialized tools, marketers need their own set of tools designed and scaled to efficiently uncover valuable insights from a mountain of data. However, in order for these “binary miners” to produce ongoing value up the chain, they need a technology stack that can do the job in real time… as in milliseconds to minutes.
Therefore, choosing the right tech stack is critical. And with a whole range of high-performance alternatives to choose from, discovering the right technology to invest in can be a treasure hunt all on its own.
To help make that search a little easier, IBM teamed up with Semphonic to create a whitepaper that accomplishes the following objectives:
- Look at the reasons why analyzing digital data is challenging.
- Show why some of the attributes of a new generation of big data systems are responsive to these challenges.
- Use this to develop a set of key decision vectors for choosing an appropriate digital technology stack for your data.
- Lay out a series of the most common digital marketing data use cases and highlight the key decision factors for each.
- Discuss the decision framework as it pertains to big data
The goal of this paper is to provide today’s enterprise marketing and IT organizations with a well-defined framework for choosing a marketing digital technology stack.
As you will see, choosing the right solution involves much more than a simple evaluation of price vs. performance. It involves matching business requirements to the comparative advantages of each possible solution.