Blogs

Natasha Bishop
Big Data Strategy lead, IBM
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Natasha Bishop is a Big Data Strategy lead and moderates the popular Customer eXperience Optimization (#CXO) twitterchat. Follow Natasha on Twitter at @Natasha_D_G

Big Data & Analytics Heroes: David Vinson

November 18, 2014
David Vinson, business intelligence and analytics lead at Nike, believe that There’s a lot of new data out there—in fact, we now have access to data from the entire supply chain (from provisioning materials to build the shoe, to actually delivering the shoe on the dock, to selling the shoe). Read More

Big Data & Analytics Heroes: Leonardo Nantes

November 11, 2014
This week’s Big Data &Analytics Hero, Leonardo Nantes, IT executive of Brazilian credit bureau Boa Vista Servicios, has faced numerous challenges since the merger of two companies took place a few years ago. Boa Vista now serves hundreds of thousands of clients nationwide and handles more than three million transactions per day. Since the business involves credit ratings and personal information, big data security and integrity are paramount. Read More

Big data for social good, not for profit

October 23, 2014
Now that the Ebola virus is sitting in our backyard, the entire country is on high alert—and rightfully so, as it's no longer a disease that's plaguing people continents away, in little known countries. WHO indicates that there are 9216 Ebola cases with 4555 deaths. My first thought when I look at these statistics is: where is big data in the Ebola equation?  Read More

Big Data & Analytics Heroes: Addison Snell

October 21, 2014
Intersect360 Research studies the opportunities for high performance technologies, including high performance computing areas in science, engineering and business. CEO Addison Snell (this week’s IBM Big Data and Analytics Hero) shares his insights with us. Read More

UDF: Tiny acronym, big deal in big data

October 16, 2014
It’s easy to understand why big data is intimidating as the whole gang of JSON, SQL, YARN and UDFs (user-defined functions) invoke glazed eyes and thoughts of extraterrestrial technologies. So, even to the uninitiated, what is the big deal about UDFs? Read More

Big Data & Analytics Heroes: Steven P. Pratt

October 14, 2014
CenterPoint Energy can analyze 2.3 million smart meters at any point in time every day using InfoSphere Streams. Dr. Steven P. Pratt, corporate technology officer at  Centerpoint Energy and this week’s Big Data & Analytics Hero, shares that “ultimately what we want to be able to do is recognize issues in our system before power outages occur.” Read More

IBM Big Data & Analytics Heroes: Menka Uttamchandani

October 7, 2014
Many businesses are exploring the competitive advantages that data gives their customer experience and their bottom line. Menka Uttamchandani, VP of business intelligence at Denihan Hospitality Group and this week's Big Data & Analytics Hero, shares that “once we understand attitudes, we can reverse engineer our marketing message to reach our high potential guest as well as guests that look like them, that are not yet our guest.”  Read More

Big Data & Analytics Heroes: Ashok Srivastava

September 30, 2014
Ashok Srivastava, chief data scientist at Verizon and this week’s Big Data and Analytics Hero, shares some of the challenges of deploying big data and his role in bridging the gap to “understand where the market is and how data can be used to support that market.” Read More

Big Data & Analytics Heroes: Michael North

September 23, 2014
Michael North, senior director of broadcast planning and scheduling for the National Football League (NFL) and this week’s Big Data & Analytics Hero, asks the all important question: "How do you…find that one grain of sand?” North shares how they utilize data to deliver compelling match-ups on the best days for viewing with the help of IBM systems.  Read More

Big Data & Analytics Heroes: Phillippe Chartier

September 16, 2014
Phillippe Chartier, information delivery team lead at Canadian National Railway and this week's Big Data & Analytics Hero, tells us how they used to rely on monthly data reports, but now they operate more efficiently—in near real time—with predictive analytics. Canadian national Railway applies logical insights from their data to save fuel consumption, predict shipments and keep their trains running on time.  Read More

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