5 Game-Changing Big Data Strategies
Though the true focus of IBM's 2013 Impact Conference is "mobile" technology, Eric Sall's Wednesday session on "5 Game-Changing Big Data Strategies" was standing-room only. Sall is Vice President of Product Marketing for IBM Information Management and has been speaking quite a bit about these key big data strategies. While studying hundreds of examples of customers leveraging big data, five key use-cases have emerged.
“It’s everywhere. You hear about it on TV and radio, digital news and social media. At the moment, I think its prevalence is second only to the Kardashians’ love life,” said Sall, kicking off his session and underscoring big data's widespread popularity.
Sall went on to describe how business models are changing, shifting power from companies to consumers, as a result of the increasing volume and availability of data.
“The intersection of big data, cloud and mobile, means a consumer can stand in a retail location, search the web for product reviews, compare pricing and possibly locate a better product. While customers use the data to enhance their experience, smart companies use the data to understand and more effectively leverage the customer experience,” Sall said.
The availability of data has created another challenge for companies. Often companies must sift through huge volumes of irrelevant data to find data capable of fueling insight. In a traditional IT infrastructure, this can add time and cost to the process of storing, managing and analyzing data.
Companies that win with big data understand how to enhance their IT infrastructures by accelerating analytics, enabling more efficient administration and leveraging more cost-effective storage.
As more attendees entered the filled room, Sall went on to detail the 5 game-changing strategies enabled by big data:
1. Enrich your Information Base with Big Data Exploration - Data-driven organizations often store massive quantities of data in different areas. Big data technologies now make it possible to break through those data silos and examine the sum total of an organzition's data.
2. Improve Customer Interaction with 360 degree view of the Customer - Today, companies must view their customers in a new light and understand them in new ways. Big data allows customers to combine volumes of both internal and external data in unprecedented ways. With these new, more powerful insights, organizations can optimize every single customer interaction.
3. Optimize Infrastructure and Monetize Data - Applying analytics to machine data allows companies to create greater IT infrastructure efficiencies by identifying events of interest, using predictive models to identify anomalies and monitoring systems to understand service degradation before it occurs.
4. Data Warehouse Augmentation - Given the volume of data now available, the cost of storing data has dramatically increased for organizations. Big data technologies can be leveraged to create a pre-processing hub or staging area to examine the flood of new data. This allows organizations to identify relevant data before moving all data into a data warehouse. Queryable archives now allow organizations to offload infrequently accessed or aged data from data warehouses while maintaining its accessibility.
5. Security and Intelligence Extension - The ability to analyze ALL data means that organizations can enhance traditional security solutions to help prevent threats and fraud by analyzing data "at-rest" and "in-motion" to find associations, uncover patterns and detect potential threats sooner.
With these five, common, big data strategies illustrated, many in the audience wanted to know where (and how) a company should begin with big data. An organization's needs and current structure will often determine the path to greatest and fastest value with big data. IBM has developed several online resources to help companies assess their current infrastructure and develop a baseline understanding of how to leverage big data. Sall closed his session by presenting a slide that featured these resources:
- Big Data University
- DeveloperWorks Big Data Community
- Big Data Developer Days Events
- And of course, IBM Big Data Hub