Note, a version of this article was originally published on MarketingProfs.com
It’s hard to open a business or a technology publication these days without finding an article about the promise of Big Data. New technologies (Hadoop, Mongo, NoSQL and others) offer businesses the opportunity to analyze very large amounts of unstructured data at a scale and speed that was simply not possible just a few years ago.
The predictions are quite bold: Gartner research recently wrote “…enterprises adopting this technology to outperform competitors by 20% in every available financial metric”.
Before you embark on a big data project it is important to separate the buzz from the reality. This post explores 5 important challenges that can limit the ability of any marketer to turn the Big Data hype into insights, business value, and ultimately, increased revenue.
What is Big Data?
Big Data can be defined a group of technologies that help organizations store and process data sets that meet one of three ‘V’s:
- Volume – for example, imagine Facebook’s database of users, posts and likes. Or a credit card company’s transaction log across all customers
- Velocity – the speed of data generation. Both examples above also require a system that processes data very fast. All this data is being created in real-time, thousands or millions of items per minute.
- Variety – what is also called ‘unstructured’ data: traditional databases operate using very well-defined schemas: name, address, credit card number, etc. Big data technologies don’t require schemas, they are more flexible in this way.
Big Data at the end of the day is a database technology. And it will not replace traditional ‘SQL’ databases, because there are things that Big Data databases cannot do, like maintaining transactional integrity, which is required for credit card payments or really any kind of business transaction. Continue reading “5 Steps to Turn Big Data Technology into Business Value”