AI/IoT/Analytics

2013 Big Data Outlook

By Bill Schmarzo February 11, 2013

Since I previously wrote about the key big data developments from 2012 (Big Data Year In Review), it’s now time to look ahead to 2013.   As most folks believe, 2013 should be a “break out” year for big data.  I expect more organizations are going to aggressively move up the Big Data Business Maturity Index (see chart below).

Figure 1: Big Data Business Maturity Index

Organizations are moving beyond big data as a science experiment and starting to look for ways to integrate key big data capabilities – such as new sources of data, predictive analytics, and low-latency data – into their existing business intelligence (BI) and data warehouse environments.  Additionally, some organizations are starting to look at new ways to couple their customer, product, and operational data with advanced analytics to uncover new data monetization opportunities.

Looking Ahead Into 2013

Listed below are some key big data developments that are going to help organizations transition up the big data business maturity index in 2013.

  • Mobile is BIG!!  Mobile – and the explosion of smartphone apps – is the next big thing, and is probably the single biggest development to impact an organization’s big data aspirations in 2013 (see chart below).  Mobile apps are transforming how organizations engage with their customer, and how those customers are consuming information and interacting with companies.  Organizations are building purpose-specific, always-on mobile apps that will enable organizations to capture more data, derive more insights about their customers’ behaviors, trends and tendencies, and couple those insights with product performance data.
  • Real-time Analytics.  Probably the next big thing for 2013 (I get the feeling that there are going to be several “next big things” in 2013) is the maturation of real-time analytic platforms (see chart below).

The real-time analytics platform will enable organizations to:

  • Gather location-based data in real-time from mobile devices and networked sensors
  • Analyze location-based data in real-time, coupled with historical perspectives, behaviors and tendencies, to identify immediately-actionable insights about customers and products
  • Power real-time customer engagement with customer-specific marketing, and power an entirely new user experience that is relevant to the customer engagement moment

We have already seen real-time analytic platforms at work in business areas such as fraud detection, ad serving, and algorithmic trading.  Now that same capability is becoming more generally available, and we’re going to see the application of these real-time analytics capabilities to a number of different business applications (see sample list below).

  • Location-based Insights.  Many of these real-time, analytics-enabled applications are going to be fueled by location-based insights.  All the mobile data about customers’ behaviors and purchase tendencies, coupled with the GPS capabilities of the smartphones, will bring forth a new generation of customer-specific marketing, enabling organizations to move closer to the holy grail of “One-to-One Marketing.”  To see how prevalent mobile tracking is, just double click your iPhone button, and scroll the list of apps along the bottom of your screen that have “location tracking” enabled (22 apps on my iPhone).
  • User Experience.  User experience still doesn’t get the proper attention inside most organizations (and I’m not talking data visualization).  Mobile apps won’t only increase the avalanche of consumer and product data that organizations can capture, but will also challenge how organizations present data and insights back to their customers.  An important by-product of the mobile user interface is the ability to instrument the app to capture more information about customers and their usage behaviors in real-time.  With that information in hand, app vendors are positioned to react to immediate customer opportunities and leverage advanced analytics to provide customer recommendations and insights.
  • Let The Tools Revolution Begin!  Big data and data scientist tools are going to improve, but not necessarily from traditional vendors.  There are large amounts of venture capitalist funding behind new data manipulation, visualization, and analysis tools, with the goal of taking market share away from the traditional business intelligence vendors.  Tools like Tableau, QlikView, Splunk, and Karmasphere will deliver new functionality and capabilities to meet the demands of the data scientist community faster than traditional BI vendors because they are not held captive by their current user base and antiquated technology capabilities. For example, on February 25th, EMC Greenplum will unveil product and technology innovations that will make Hadoop bigger, better, more accessible and meaningful than ever before.  I think this announcement could be a game-changer for many folks already trained in the BI and data warehouse space.  Here’s a link to the official announcement:  “Hadoop: The Foundation For Change.”
  • Data Scientist resource gaps start to shrink due to better tools and more data science-specific training and education.  Many universities are scrambling to fill this need.  Hadoop training and training on statistical and predictive analytics is available online.  EMC offers a Data Scientist education and certification program.  Check out https://www.coursera.org/ as well.
  • Data Warehouse Modernization.  Modernizing your data warehouse will take a higher priority in 2013.  Organizations have invested tens and hundreds of millions of dollars in their data warehouse capabilities, and they are missing the opportunity to enhance that investment with big data technologies and methodologies.  Adding the ability to handle unstructured data, leveraging MPP technologies to develop a more agile data architecture, and adding in-memory computing to manage high-velocity data feeds are just a few examples.  Check out my previous blog, “The Data Warehouse Modernization Act,” for areas where I expect organizations to embrace big data capabilities to advance their existing data warehouse and BI investments.

Big Data in 2013

2013 looks to be a watershed year for big data.  And for me personally, it could mean some new and very interesting big data opportunities.  I hope that more organizations see these big data developments as an opportunity to move beyond big data as a science experiment, and look for business opportunities that can re-wire the organization’s value creation processes.  Watch this space!!

By the way, for folks interested in learning more about the Big Data Business Maturity Index, I will be speaking at the Strata conference in Santa Clara on “The Big Data Business Maturity Index.”  My session is Tuesday, February 26 at 10:00.  Stop by if you want to learn more about how to leverage the Big Data Business Maturity Index to 1) ascertain where you are today in order to 2) develop a roadmap to big data business success.  And if you do come, please be sure to talk to me after the session.  I’d love to hear your thoughts about where we are going in this big data world!!

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  1. Pingback: 11 February 2013: InformationWeek | Tap the 90