Instrumented Interconnecteds Intelligent

Beth Smith, General Manager, Analytic Platforms, IBM

Beth Smith, General Manager, Analytic Platforms, IBM

By Beth Smith

Recently, a friend shared a story about his 7 year-old daughter who had pleaded for a mobile phone. When he said no, she asked ‘Please, how old were you when you got your first one?’ He responded, “32.”

Who would have ever foreseen such a rapid pace of innovation and adoption? But the same can be said for the conversation around big data.

Not so long ago, organizations relied on the data they could easily get their hands on. Now they are able to glean meaningful insight from videos, documents, and even doctors’ handwritten notes.

At IBM, we saw the potential of big data early on and committed to Apache Hadoop and to building an analytic ecosystem that leverages common tools such as SQL and R. As a result, we are enabling business and technical users to explore and interact with data to understand patterns and predict outcomes.

This week at Strata + Hadoop World in San Jose, I am excited to hear how more organizations are innovating by putting Hadoop and big data technologies to work in their business.  How industries like telecommunications, automotive and healthcare are leveraging Hadoop and analytics to offer new products and services, or to interact with consumers in more effective ways. Hadoop is becoming more than just a silo-ed data platform, it is a critical component of a broader analytics platform.

For our part at IBM, the announcements we made earlier this week are focused on helping clients get positive results faster. By putting analytics in the hands of data scientists and business analysts, we are enabling them to extract the full potential of their data. We know that by enabling data scientists with a full range of massively scalable machine learning algorithms programmable via the “R” suite of data visualization and analysis software, they can find patterns by looking at all the data, not just sample sets.

And R is also supported by IBM SPSS predictive analytics software, making it easy to build models for business, such as fraud detection in banks and financial institutions, customer churn prediction in telcos, or customer segmentation and market basket analysis in retail.

The very purpose of innovation is to open up new opportunities for everyone. We are enabling people with diverse backgrounds to explore and interact with data to uncover patterns, find answers and gain insights that can help their work; shape their business; transform their industry.

The pace of innovation is rapid. The next step in our journey with big data is to ensure we gain the value from innovation at the equal pace.

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