Am I Ready for Big Data?

May 17, 2015   //   by BradP   //   Big Data, Blog, Business Intelligence  //  1 Comment

The Hot Topic for the past few years in Business Intelligence has been “Big Data”. Even though this term has been discussed quite a bit, there is still some confusion about what “Big Data” really is. This post lays out my understanding of big data and how this subject has evolved since it was introduced in 2011. Hopefully after reading this you will be able to answer the question: “Am I Ready for Big Data”?

The term big data was coined by the ├╝ber-management consulting firm McKinsey and Company in a research paper published in May 2011. The key takeaway from this research paper is that companies are generating much larger volumes of data than have been produced in the past. Systems such as ERP, CRM, SCM, and other three-letter acronym systems are capturing everything in a digital format. In addition to the actual transactions, these systems are generating a tremendous amount of “exhaust data” which is a by-product of other activities. Items like RFID tags, hand-held scanners, and smartphones are contributing heavily to this exhaust data.

This report focused on the sheer volume of data being captured but big data has evolved and now encompasses the variety of data that’s available. Additional data is now available in unstructured sources such as blogs and social media applications like Facebook and Twitter. Lately big data has become more about capturing what people are saying on social media.

Another “v” word associated with big data is velocity which deals with real-time (or near real-time) data warehousing. I don’t consider velocity to be unique to big data because real-time data warehousing can exist without volume and variety.

To generate business value from big data (either volume or variety), organizations need to have a mature BI program already in place. Certain steps need to be climbed before organizations can successfully implement big data sources into their Data Warehouse.

Am I Ready for Big Data?

If your BI program is in its infancy, do not attempt to implement big data – especially data of the unstructured variety. Concentrate on the data that’s already available to your organization; preferably data that’s in your control and in your databases. BI projects are an iterative part of a BI program and it’s best to start with data that’s familiar and understood by your organization.

Start by developing a BI Roadmap that will outline the steps necessary to implement a successful BI program. If your organization is new to BI, conduct a Readiness Assessment to determine if your organization is ready to embrace Business Intelligence.

MIPetersen Consulting is able to assist your organization with both of these activities. Please leave a comment or send an email using the quick contact form below.

1 Comment

  • “It’s like a giant fishing net dragging the bottom,” Warnock says. “There’s big fat tuna and swordfish in there, but also mussels and lobsters and flounder. They’re just scraping data and they don’t know yet what they’re going to do with it. The correlations that could be drawn from that data haven’t even been determined yet.”

Leave a comment

You must be logged in to post a comment.