If you’re tired of hearing about what a big deal big data is going to become, we’ve got good news to share — that conversation is now over.
Big data has gone mainstream, say the experts. Ditto for big data crunching Hadoop.
Forrester analyst Mike Gualtieri made it official last month when he declared that the economic benefits of Hadoop will make adoption essential, not optional, for enterprises as they move into 2015.
And putting dollars aside, big data analytics are quickly becoming part of everyone’s job, says Tom Davenport, a Distinguished Professor of Information Technology and Management at Babson College and author of Big Data at Work. He asserts that we are entering the Analytics 3.0 era, in which insights can be delivered anytime you need them via any device.
A Sampling of Popular Posts
At CMSWire this year, we wrote all about the advances that big data was making in the enterprise and the challenges that come along with it. Here’s a glimpse at what some of our more popular articles asserted.
1) I took a look at the size of the footprint that various vendors had in the exponentially growing big data market. We were surprised to learn that the bark and the bite didn’t match. That generated plenty of interest in my story, Who Leads the Big Data Market? (Probably Not Who You Think). Tweet to Virginia Backaitis.
Can you be a “born in/for the world of big data” provider and rank high on the list? The innovators will, no doubt, say yes (otherwise they best be looking for new jobs), but as they work to build their enterprise relationships, established enterprise providers like IBM, HP, EMC and Microsoft are scurrying to beef-up their own big data plays.
2) Siobhan Fagan investigated the question of the year. What does it take to become a data scientist? She interviewed superstar practitioner Claudia Perlich to get the answer in her article One Woman's Path to Data Science. Tweet to Siobhan Fagan.
Perlich has been in the field for 18 years now and it's only recently that the demand and the interest have peaked. "Back then I was just a geek, now all of a sudden I have a sexy job," she said.
3) Joanna Schloss told us that big data is no longer the sole domain of big companies and that there were lessons to be learned from early adopters in her story 5 Lessons About Big Data from Big Companies. Tweet to Joanna Schloss.
Companies who are later to the game in the adoption curve of any technology cycle have opportunities to learn from those who came before them. In the case of midmarket companies about to embark on big data projects, that means capitalizing on lessons from their enterprise forerunners.
You have massive amounts of data, but what good is it if you can't access, analyze and learn from it? What good is it to make the right decision, only after the opportunity has passed?"
5) Nenshad Bardoliwalla investigated the challenges business analysts face when dealing with large volumes of data coming at them from a large variety of different sources in Rescue Your Data From the Big Data Landfill. He suggests that we need a new strategy. Tweet to Nenshad Bardoliwalla.
These professionals now have to deal with a data landfill — mountains of data that enterprises are collecting and trying to use to make business decisions. This fast changing world requires a new strategy that goes beyond the current data preparation methods used by IT.
6) Scott K. Wilder wrote a brief and a “how to” on using insights gleaned from big data to individualize customer interactions in Personalizing Customer Experience with Big Data. Tweet to Scott K. Wilder .
The more they can understand about how data can be pulled from a system and displayed on a screen, the more effective they will be in selling their products and services. This will take time. This will require marketers to get their hands dirty, get under the hood and understand more than the fundamentals of big database marketing.
Metadata is the best way to identify little data that becomes big data. Little data provides structure to what becomes big data. Invest the time, energy and resources to identify, define and organize your assets for discovery and increase their value.
8) Manny Chhabra argued that big data is useless unless you have the right skills to integrate and analyze information. He went into detail in What Skills You Need to Extract Business Value from Big Data. Tweet to Manny Chhabra .
IT professionals need experience with data mining and analysis to help their companies discover useful information, draw conclusions and support sound decision making. This means backgrounds with technologies like Hadoop and MapReduce.
9) Svetla Yankova noted that the era of data driven marketing in which game-changing insights deliver to their full potential isn’t quite here yet in How Big Data Can Make You a Better Marketer. Tweet to Svetla Yankova.
Before we can tap the results of big data, we need to examine the perspectives that are used to fill the funnel — growth and sales — and think about some of the fundamental shifts that are taking place. Then we’ll more clearly understand how big data fits in.
10) Dom Nicastro interviewed Sandro Catanzaro, founder and SVP of Analytics and Innovation at DataXu and discovered four ways to use data and analytics to improve digital marketing in his article 4 Ways Data and Analytics Improves Your Digital Marketing. Tweet to Dom Nicastro.
“As a digital marketer, you are asked to create display campaigns that positively affect brand awareness. You are asked to make optimal use of your advertising budgets by market. You are asked to analyze customer behavior and media consumption.”