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Friday 24 May 2013

Big Data-Beyond Hadoop-In Response to the articles- 1

Big Data-Beyond Hadoop-In Response to the articles read.

  This is with reference to where the Big data market is heading to beyond Hadoop. why is it so?

   Barry Devlin Mentioned that fundamentally there are 3 kinds of data sources for Big Data. i.e For large sets of data to be processed.
1) Human-Sourced Information
2) Process-Medidated Data
3) Machine Generated Data

Now all these are poorly governed or managed themselves so need to be enhanced with traditional process-mediated data
to deliver useful and relevant business analytics.So the market may need to shift from big data startups and small vendors to more established vendors with enterprise-scale technologies
for semantic and physical integration of multiple data types from multiple sources.

Now the interesting statement is here "Google and Facebook, whose needs have exceeded the capabilities of file-based tools like Hadoop. A new wave of tools—Dremel, Caffeine, Pregel, Spanner and Prism—may be upon us as the biggest big data proponents inexorably move the needle from a batch-oriented, eventually consistent paradigm toward a distributed but ACID-compliant database mind-set."

Now,Big Data Beginners asking the below questions.

So Now is it that Hadoop is not really that promising that it was looking like?
If I go by market hype, Hadoop can solve all big Data problems. Is not it?

Source link: http://ow.ly/lmlgf

Open for comments.

Friday 3 May 2013

Skills required for Big Data Experts

This post is intended to gather the skill set information required for any Big Data experts that various organizations are looking for.

 A solid understanding of Algorithms and Data Structures
A solid understanding of Operating system and networking fundamentals
Hands-On experience on Hadoop and it's ecosystem, CASSANDRA, Any NO-SQL family
Understanding of performance optimization at a scale
Programming skills in Java, Map Reduce