Would you agree if I say that 2013 is the year of big data? There were talks on big data last year and now, it’s the center of data analytics as we know it. Both private and public sectors alike would want to tap into predictive analytics, of having access to information that can be used not only in growing business and customer base, but also to enhance homeland security, law enforcement, finance, health care and a whole lot more. The race is on in finding value in the vast volume of data, like ripe apples ready for the picking. We’ve only scratched the tip of the iceberg and we haven’t unlocked big data’s fullest potential yet. One can only ask if outdated policies can really keep up with these new technologies (soon?)
Responding to the Big Data Challenge
Are Fortune 500 companies making big data investments like some digital gold rush? One thing is for sure, business decisions are now data-driven and they need to measure what they want improved. Simply put, data is everywhere and the world just got bigger as we see structured and unstructured data proliferate online documents, websites, social media, mobile and relational databases. To be highly productive where big data is concerned will mean finding the right data scientist to interpret things accordingly. The issue here is not so much about a lack of talent where big data initiatives are concerned, but organizational alignment – of making sure that business and technology will work together for a common goal. This is still a work-in-progress among many who are trying to manage data and create an environment with the greatest probabilities of success.
Big Data, Bigger Myths
Just as there’s huge enthusiasm over big data, there are those who call it a hype. I was just reading this post by Matthew on how President Obama really beat Romney – and it’s curious to see bias in the interpretation of data presented. I’ve been following all these talks about the big data buzz and compiled these myths as follow:
1. Size matters – Not really; bigger volumes of data doesn’t necessarily mean it’s valuable.
2. You Have to Know Hadoop – while this open-source Apache software is great for working with big data, you don’t need to master it just for you to leverage customer data to improve your business ROI.
3. It is Unstructured – which is not really accurate. Big data is multi-structured as it can come in any (and many ) forms
4. It’s only used for analyzing social feeds or user sentiment – which big data can do, but it has more to offer than that ( This article on Forbes shows you other ways of using big data ).
5. There’s an Ultimate Solution – The complexity of big data shows us that there’s just no silver bullet to solve it. You need to have a dynamic environment to effectively collect, manage and draw insights from big data
If you collect quality data, you’ll get quality results. While these myths abound, let me say this: Knowing is Better than Guessing. Like it or not, big data is here to stay. It may be a tough road to take as you switch from information overload to focused data. In the end, everyone wins. Just take a holistic approach, be open to new data patterns and integrate the old into the new.
Then, reap bigger rewards..