With one half of 2013 behind us, let’s take a look at what has been on the top of your mind over those six months. All week long, we will be reviewing the most read, most watched and most listened to content on IBM Big Data Hub. Today, we’ll look at the top 10 most popular podcasts.
Conversations around big data are shifting from "what is big data?" to "what can I do with big data?" Five key use cases have emerged that hold high potential value for many organizations. Eric Sall, vice president of product marketing at IBM, describes those high-value uses for big data.
In this episode of "Talking Big Data," we turn over the microphone to one of our clients, Jean-Marc Blaise, an experience DB2 user and consultant. Like many database administrators, users and consultants, he has questions about "big data." He will pose those questions to Leon Katsnelson, IBM program director for big data and cloud.
The IBM Institute for Business Value (IBV) is embarking on its fourth annual survey on analytics and big data. Rebecca Shockley, Global Research Lead at IBV, gave a preview of the objectives for the 2013 survey. She explained they will be looking into how organizations are executing and what it takes to execute on big data analytics within an organization, be it a small company or a large, multinational corporation. IBV will also examine how data are brought together and what skills are involved in deriving value from it. They will also look at the leadership and culture of organizations, striving to determine the attributes that lead some companies to succeed while others may flounder. Listen to the podcast to learn how you can participate and what benefits you will get from being a part of the 2013 survey on big data and analytics, then register to take the survey: ibm.com/2013bigdatasurvey
In a Forbes blog post titled, "Data Science: Buyer Beware," the author expressed a great deal of skepticism about the sudden popularity of data science. He called data science "yet another business fad that forgets people, and probably just as destructive." Understandably, this rankled many data scientists. We talked with noted data scientist David Smith, vice president of Marketing and Community at Revolution Analytics, to get his opinion on this "buyer beware" warning.
Operations analysis, one of the top five use cases for big data, is about analyzing a variety of machine data to get improved business results. The key is combining machine and business data, which allows you to put insight right into the hands of the operational decision maker. In this podcast, Christy Maver, IBM big data product marketing manager, describes what operations analysis entails and the primary benefits of employing it. She also relates several examples and gives advice on how to get started with operations analysis.
Michele Chambers, co-author of "Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Business," talks about the market and technology factors that make now the prime time for big data analytics.
Data Exploration is one of the top five business use cases for big data. Stacy Leidwinger, product marketing manager for IBM Data Explorer, describes the challenges that many organizations face, and the four key steps they should take when beginning a data exploration project.
"Data warehouse augmentation" is one of the top five business use cases for big data. Its purpose is to extend the value of existing data warehouses. Christy Maver, IBM big data product marketing manager, explains how data warehouse augmentation can help lower costs, provide the ability to perform analysis on more and new types of data, and she also describes three primary scenarios where data warehouse augmentation makes sense.
Security intelligence with big data is the ability to lower risk, detect fraud and monitor cyber security in real time. Organizations can augment and enhance cyber security and intelligence analysis platforms with big data technologies to process and analyze new types (e.g. social media, emails, sensors, Telco) and sources of under-leveraged data to significantly improve intelligence, security and law enforcement insight. Sandy Bird, chief technology officer of IBM’s security systems division, gave an overview of security intelligence, which is one of the top five use cases for big data. He discussed some key questions an organization should consider, how the threat landscape has changed in recent years, and how organizations are using big data to address cyber security challenges.
A big data platform, because of its ability to consume and process more data from both static and streaming sources, enables organizations to get an "enhanced 360-degree view of the customer" that has not been possible previously. Mark Myers, IBM big data product manager, describes this key use case and gives several examples of how today's new big data technology differs from and complements CRM and other existing products.