Challenge: Making Big Data More Agile
One of the many challenges corporations face today is big data. How do we collect it? What do we do with it? How can we make it work for us? Are all questions companies are currently struggling with answering. However, a new trend is gaining popularity that might help organizations answer some of these difficult questions.
The rate of change in the business environment is only increasing. Social media and mobile technologies have made it more difficult for organizations to stay on top of trends, and adapt. Businesses have begun to place a large emphasis on data. The logic behind this move makes complete sense: the more data you have, the better your decisions will be. However, with data now coming from multiple channels, and of different types, it can end up very messy very quickly costing them time and more importantly money.
According to a recent piece by Ernie Schell, businesses are adopting a new technique to deal with this problem. Initially, “most organizations decided quite a while ago to just dump data into spreadsheets and let each user do their own thing.” This works pretty well for smaller companies, but creates chaos for larger ones – trust me, having worked for a fairly large company that still relied substantially on excel sheets and it’s a nightmare. Schell aptly points out “when you have more than a half dozen or so people doing their own thing, you quickly run into apples and organs comparisons, which everyone knows can be misleading and dangerous.”
As organizations grew to combat this problem or unequal comparisons they adopted dashboards. By establishing a unified set of data, employees are able to quickly and easily draw data comparisons. Dashboards also allow everyone to select their own variation of how the data is presented there by allowing for quicker decision making by managers. However, Schell argues that even a “drill-down type of analysis that relies on pre-set data parameters” can be “somewhat limiting.”
Today, we’re seeing a new trend in data collection and analysis emerge – “agile analysis”. This new trend is based on the concept of “agile development”, which focuses on the establishment of a close relationship between developers and their audience allowing for feedback at multiple review points. With the coming of age of social media, the internet has fundamentally changed. It’s evolved from a series of linked pages that you gather data about, to a mash-up of rich applications. According to Schell, this will only get more complex as “the impact of Social Media will only continue to add velocity, density, and volume to the data analysis mix.” As data gets more complex, the key will be to make data more agile.
How’s this done? According to Schell, it’s all about finding a business intelligence platform that “reflects these changes.” For example, allowing decision-specific applications to be joined together to form flexible and evolutionary platforms, or by incorporating analytical applications that can be added, removed and updated quickly. Schell believes “What is essential is the ability to rapidly source information, connect it to other information in both a tightly and loosely integrated fashion, and quickly connect BI applications together.” This combination is going to be critical in the ever shifting business environment.