MapR recently invited BigDataPartnership’s Christian Prokopp to blog about the 6 steps to big data success. It makes interesting reading, and focuses on the business and not just the technology – which is merely the means to delivering value to the business.
Category Archive for: Apache Hadoop
The BigStep bloggers added a new entry to their Expert Interviews when they talked to Big Data Partnership Principal Consultant, Christian Prokopp. You can read what Christian shared about Hadoop, Big Data adoption challenges, alternative and future trends here: http://blog.bigstep.com/expert-interviews/expert-interview-christian-prokopp/
I spend most of my life – not just the working day – explaining, cajoling and describing how the new evolution of data management is in fact a revolution. It’s a revolution where everybody is going to be affected, in many areas of their working and home lives. Part of that time I spend on…
A role for Hadoop in seismic imaging and monitoring workflows Seismic imaging data presents significant data management and processing challenges. Terabyte-scale high-resolution datasets are routinely summarised early in workflows due to limited computing capabilities, losing valuable signal. This loss of detail restricts flexibility for geophysicists, increases numerical uncertainty and ultimately diminishes accessible insights. To test…
The advances in big data technology are opening up new ways to collect and transport large amounts of data more efficiently. This revolution has boosted research and development of real-time algorithms and methods. Traditionally, machine learning algorithms were not designed for real-time processing. In fact, data science competitions (e.g the Netflix prize, Kaggle) were criticised…
With businesses becoming increasingly sensitive to customer opinion of their brand, monitoring consumer feedback is becoming ever more important. Additionally, the recognition of social media as an important and valid source of customer opinion has brought about a need for new systems and a new approach. Traditional approaches of reactive response to any press coverage…
Social profiles tell us a lot about the interest of its owner and also about people/organisations they follow and people who are following them. This blog post is a summary of what information you can get by collecting and analysing your customer profiles in 24 hours. In fact, after unlocking of the data, this process…
Hadoop is a grassroots phenomenon that emerged in the social networking and consumer Internet world. As always, there are early adopters who take risks on the cutting edge, and there are more conservative organizations watching the pioneers from the sidelines. This played out in 2011 as early customer experiences with Hadoop were shared via conferences,…
With the increasing popularity and the addiction of companies towards Hadoop, also Hadoop being an unanimous solution for Big data platforms makes the Hadoop development team to focus on the current architectural deficiencies and make Hadoop free from such underlying architectural issues. In that path a new Hadoop MapReduce version has taken birth MapReduce 2.0…
Joins:- ======= Joins is one of the interesting features available in MapReduce. Joins performed by Mapper are called as Map-side Joins. Joins performed by Reducer can be treated as Reduce-side joins. Frameworks like Pig, Hive, or Cascading has support for performing joins. Before diving into the implementation let us understand the problem throughly. If we…
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