Both ODI and the Hadoop ecosystem share a common design philosophy. Bring the processing to the data rather than the other way around. Sounds logical, doesn’t it? Why move Terabytes of data around your network if you can process it all in the one place. Why invest millions in additional servers and hardware just to transform and process your data?
In the ODI world this approach is known as ELT. ELT is a marketing concept (more...)
My client Teradata bought my (former) clients Revelytix and Hadapt.* Obviously, I’m in confidentiality up to my eyeballs. That said — Teradata truly doesn’t know what it’s going to do with those acquisitions yet. Indeed, the acquisitions are too new for Teradata to have fully reviewed the code and so on, let alone made strategic decisions informed by that review. So while this is just a guess, I conjecture Teradata won’t say anything concrete (more...)
The idea of clouds “meeting" big data or big data "living in" clouds isn’t simply marketing hype. Because big data followed so closely on the trend of cloud computing, both customers and vendors still struggle to understand the differences from their enterprise-centric perspectives. Everyone assumes that Hadoop can work in conventional clouds as easily as […]
Data lakes, like legacy storage arrays, are passive. They only hold data. Hadoop is an active reservoir, not a passive data lake. HDFS is a computational file system that can digest, filter and analyze any data in the reservoir, not just store it. HDFS is the only economically sustainable, computational file system in existence. Some […]
I was recently invited to speak about big data at the Rocky Mountain Oracle User's Group. I presentedto Oracle professionals who are faced with an onslaught of hype and mythology regarding Big Data in generaland Hadoop in particular. Most of the audience was familiar with the difficulty of attempting to engineer even Modest Data on […]
In the 1960s, Bank of America and IBM built one of the first credit card processing systems. Although those early mainframes processed just a fraction of the data compared to that of eBay or Amazon, the engineering was complex for the day. Once credit cards became popular, processing systems had to be built to handle […]
Scoop, Flume, PIG, Zookeeper. Do these mean anything to you? If they do then the odds are you are looking at Hadoop. The thing is that while that was cool a few years ago it really is time to face it that HDFS is a commodity, Map Reduce is interesting but not feasible for most users and the real question is how we turn all that raw data in HDFS into something we can actually (more...)
Hi Fellow Big Data Admirers ,
With big data and analytics playing an influential role helping organizations achieve a competitive advantage, IT managers are advised not to deploy big data in silos but instead to take a holistic approach toward it and define a base reference architecture even before contemplating positioning the necessary tools.
My latest print media article (5th in the series) for CIO magazine (ITNEXT) talks extensively about need of reference architecture in (more...)
Over the last few years there has been a trend of increased spending on BI, and that trend isn't going away. The analyst predictions however have, understandably, been based on the mentality that the choice was between a traditional EDW/DW model or Hadoop. With the new 'Business Data Lake' type of hybrid approach its pretty clear that the shift is underway for all vendors to have a hybrid
Before I joined Cloudera, I hadn't had much formal experience with Big Data. But I had crossed paths with one of its major use cases before, so I found it easy to pick up the mindset.
My previous big project involved a relational database hooked up to a web server. (more...)
Next week is Strata + Hadoop World which is bound to be exciting for those who deal with big data on a daily basis. I’ll be spending my time talking about Cloudera Impala at various places so I’m posting my schedule for those interesting in catching about fast SQL on (more...)
I haven’t had much time over the past year to do many blog posts, but in the next few months I’ll be doing a few talks about what I’ve been working on over that time, Cloudera Impala, an Open Source MPP SQL query engine for Hadoop. Hope to see (more...)
This year’s R User Conference happened in Albacete (Spain), gathering R professionals and enthusiasts all over the world since 2004, when it first began in Vienna. The sponsors this year were REvolution analytics, Google, R-Studio, Oracle, and TIBCO. Other companies like OpenAnalytics and Mango Solutions were also present with a booth stand. Besides sponsoring the (more...)
“It’s the analytics stupid!” Obviously the offense is not intended at the dear reader. It’s a wake up call for all the people excited with Hadoop and lack BI vision. The BI people that lack infrastructure vision are also to blame. Blame for what? We’ll see later in this (more...)
Since I joined a Big Data Event : Frankfurter Datenbanktage 2013 - I started to take also a look to non-relational technics too. The RDBMS is not for every asepct the correct and fitting and fulfilling answer to all data related IT challenges.
Frequently I wondered about how facebook (more...)
What’s all the fuss about Big Data?
Big Data is the collective term for very large and potentially complex data sets that are deemed to be so large that it’s difficult to handle the data using traditional tools and applications such as Relational Database Management Systems. Scientists in the fields of physics, genetics and meteorology were previous examples of those that encountered Big Data.
Back in March 2012 I experienced an air milage overflow: almost straight from Madrid I’ve picked a flight to Israel to speak at a Big Data conference, only to be back in Lisbon and fly again to Johannesburg in South Africa to meet several customers in the retail and manufacturing area. Back to Lisbon I packed again to London [...]
In times of hysteria people tend to use their reptilian brain. This sub-brain, that has been with us since we were fish, or tadpoles, it’s what kicks in when we face the unknown. In computer science or information technology, organizations tend to hold down to emotions and less and less in reasoning. Could it be [...]
This past week I spent some time setting up and running various Hadoop workloads on my CDH cluster. After some Hadoop jobs had been running for several minutes, I noticed something quite alarming — the system CPU percentages where extremely high.
This cluster is comprised of 2s8c16t Xeon L5630 nodes with 96 GB of RAM running CentOS Linux 6.2 with java 1.6.0_30. The details of those are:
$ cat /etc/redhat-release
CentOS release 6.2 (Final)
$ uname -a
Linux chaos 2.6.32-220.7.1.el6.x86_64 #1 SMP Wed Mar 7 00:52:02 GMT 2012 (more...)