MapReduce

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HStreaming is an analytics platform build on top of Hadoop and MapReduce. It allows analyses on unstructured and structured data in real-time, adding a significant improvement to Hadoop and MapReduce, as these tools are built for batch-processing.[read more]

data flow

With big data come a few challenges. What can we do when data flows faster than it can be processed? There is a solution that benefits everyone (users, companies such as Google, Amazon, Netflix, Facebook or Twitter, and clients): better use of data science.[read more]

Hadoop toolbox

Hadoop and Big Data have almost become synonymous. But Hadoop is not just Hadoop now. Over time it has evolved into a big herd of various tools, each meant to serve a different purpose. But glued together they give you a powerpacked combo. Here's my short intro to some very useful tools.[read more]

Hadoop, meet Ubuntu

Now, here is a treat for all you Hadoop and Ubuntu lovers. Last month, Canonical, the organization behind the Ubuntu operating system, partnered with MapR, one of the Hadoop heavyweights, in an effort to make Hadoop available as an integrated part of Ubuntu through its repositories.[read more]

Big Data Analytics

We are reaching a crossroads in the world of analytics. Over the years, we have seen analytic environments and data environments begin to merge through the advent of in-database processing within relational database engines. But is this causing a case of "2 steps forward, 4 steps back"?[read more]

Big Data and CRM

Customer Relationship Management has always involved data, but most of it used to be structured data; new techniques make it possible to process, store and analyse massive amounts of unstructured data as well, which means CRM can finally become a true revenue driver.[read more]

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All the big data efforts of Walmart are a good example of the massive possibilities of what can be done if big data is truly incorporated in the DNA of the company. Already, Walmart is able to optimize the local assortment of Walmart stores based on customer commentary on social media.[read more]

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For every successful case study listed in Harvard Business Review, Fortune or the like on “Big Data” success, there are likely thousands of failures. Hidden behind all these “success stories,” there is a figurative graveyard of big data failures that we never see.[read more]

Individuals skilled at data manipulation, modeling and programming, often titled “data scientists,” are in great demand due to the growing need to analyze and get value from big data. But how important is it that they understand emerging technologies such as Hadoop?[read more]

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Facebook has admitted to a major bug in Insights that resulted in inaccurate data. But the social analytics problem is the second bit of evidence that Facebook is struggling with making its own massive data store. Facebook engineers also admitted struggling with Graph Search.[read more]

Here’s a compilation of my five favorite YouTube videos on the topic of Big Data, including a talk about Hadoop and MapReduce given by Robert Scoble, the CEO of Cloudera.[read more]

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At Teradata Partners Conference 2012 held this week near Washington D.C., Simon Zhang’s talk on “Data Sciences and Analytics Evolution @LinkedIn,” provided many useful insights for oraganizations wanting to expand into the space of decision making using Data Analytics built on Big Data ecosystems.[read more]

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Some emerging “Big Data” platforms offer the perfect tool for monitoring public sentiment toward a company or brand, even in the face of the rapid explosion in data volumes from social media, which could easily overwhelm traditional BI analytics tools.[read more]

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University of California computer scientist Dr. Larry Smarr is a man on a mission—to measure everything his body consumes, performs, and yes, discharges. For Dr. Smarr, this data collection has a goal –to fine tune his ecosystem in order to beat a potentially incurable disease. Is this kind of rigorous information collection and analysis the future of healthcare?[read more]

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Can “Big Data” technologies such as MapReduce/Hadoop, or even more mature technologies like BI/Data Warehousing help banks make better sense of their own complex internal systems and processes, much less tangled and interdependent global financial markets?[read more]