BTW, we did our #CIOchat Twitter chat on this topic last week. As usual, there was no consensus, which I attribute to a healthy and candid discussion. Use the hastag #CIOchat between 2-3 p.m. EDT last Thursday (6/25). We'll be back at the same time this Thursday.
I recently had a conversation with a guy I have known for years. He has become, in middle age, what is known in the business as a “serial CIO.” These are CIOs who quickly move from job to job, frequently for the wrong reasons. I hear from him several times a year. Right now he is, as is frequently the case, out of a job. In fact, he has landed and lost three CIO positions over the past five years. He has now been unemployed for over a year and is finding that his past has rapidly caught up with him.
It’s no secret that big data offers big value. But enterprises know that to exploit it, they must capture a tremendous volume of data, in myriad forms, and contain it in a database capable of running complex and comprehensive analyses.
Today, costs of scaling traditional systems have grown prohibitive. So the pressure is on to find a new solution. Enter: Hadoop.
Technology has profoundly transformed the world in recent years. In the last decade alone, mobility, cloud, social media and big data have changed the landscape of IT dramatically. One group affected perhaps the most by the ever-changing landscape is the CIO.
There’s a lot of noise out there about DevOps right now—and with good reason. With its goals of removing IT bottlenecks and putting the business back in charge of innovation speed, DevOps focuses on putting new ideas and tools into action faster and more efficiently. The idea of extending “agility” from conception to delivery improves IT’s ability to respond to business needs.
Think about how its principles can yield meaningful results for your business.
The business intelligence insights your organization has in all the data it stores can lead to game-changing opportunities--if your analytics system has the power to uncover them. Traditional data analytics are often maxed out by big data, unable to return results in a timely fashion, resulting in missed business opportunities. Business and marketing leaders can’t execute on new ideas to generate more revenue because IT can’t support their requests to add new data sources to existing queries.