When talking about big data, it is easy to talk theoretically about what to do with it. Theory is all nice and dandy, but often the best advice comes from those with real world and hands-on experience with a topic. TechTarget recently published an e-guide entitled, “Big Data Challenges and Pitfalls.” The first article in the e-guide is entitled, “Dealing With Big Data Challenges: Real World Strategies and Advice” by Mark Brunelli. There are four tips and strategies that Mr. Brunelli gives so that you can have the highest success rate of finding patterns in big data.
- All of the information that yo have gathered does not need to be stored in a data warehouse for your users to analyze. “as you load your data warehouse or other databases with large volumes of information, start the analytics process by analyzing a subset of key business data for meaningful patterns and trends to prove the value of the big-data approach and gain experience in overcoming big-data challenges.”
- Working with big data is a lot like working with clean laundry. You do not randomly shove clean laundry into a dresser drawer, but you classify and put like articles of clothing together. Big data should not just be put into data warehouse or data mart, but first it should be classified and categorized in terms of how it is used and what business purpose it serves.
- For cost-effective, efficient and scalable big data management use open source tools such as Hadoop, MapReduce and NoSQL data stores which leverage distributed computing.
- Hold monthly user group meetings. A huge hurdle to optimizing big data is know what data is needed and the best way to know what data is is by understanding your users and how they are hoping to use big data.
If big data is a topic that interest you, I’d definitely recommend checking out this article as it is packed with helpful information about how different companies are facing challenges with big data in the real-world and what they are doing to work around it.