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...)
Permission issues is one of the key error , while setting up Hadoop Cluster, while debugging some error found below table on http://hadoop.apache.org/ . It’s a good scorecard to keep handy.
Permissions for both HDFS and local fileSystem paths
The following table lists various paths on HDFS and local filesystems (on all nodes) and recommended permissions:
In every change there are hype machines that over play and sages who call doom. Into the Big Data arena steps David Searls to proclaim that Big Data is a myth and simply hype which is set to burst in an article over at ZDNet.
But big data, he said, is nothing more than the myth that collecting vast amounts of data can help companies know customers better than those customers even know
My paper on NoSQL and Big Data won the Editor’s Choice award at ODTUG Kscope14. Here are some key points from the paper: The relational camp made serious mistakes that limited the performance and usefulness of the relational model. NoSQL is based on the incorrect premise that tables in the relational model must be mapped to […]
I'm going to state a sacrilegious position for a moment: the quality of data isn't a primary goal in Master Data Management
Now before the perfectly correct 'Garbage In, Garbage Out' statement let me explain. Data Quality is certainly something that MDM can help with but its not actually the primary aim of MDM.
MDM is about enabling collaboration, collaboration is about the cross-reference
There is a massive amount of IT hype that is focused on what people see, its about the agile delivery of interfaces, about reporting, visualisation and interactional models. If you could weight hype then it is quite clear that 95% of all IT is about this area. Its why we need development teams working hand-in-hand with the business, its why animations and visualisation are massively important.
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
As Hive metastore is getting into the center of nervous system for the different type of SQL engines like Shark and Impala. It getting equally difficult to distinguish type of table created in Hive metastore. Eg. if we create a impala table using impala shell you will see the same table on hive prompt and vice versa. See the below example
Step 1 : “Create Table” in Impala Shell and “Show Table” (more...)
"Real-time" its a word that gets thrown about a lot in IT and its worth documenting a few of the different ways it gets used
This is what Real-time Java was created to address (along with Soft Real-time) what is this? Easiest way to say it is that often in Hard Real-time environments the following statement is true
If it doesn't finish in X milliseconds then people might die
There are various views going around on what a Data Scientist is and what their value is to an organisation and the salaries they command. To me however asking 'what is a Data Scientist?' is like asking 'What is a Physicist?' sure 'someone who studies Physics' might be a factually accurate but pointless definition. How does that separate someone who did Physics in High School from Albert
One of the things that always stuns me in IT is how people don't appear to like change. Whether it was the EAI folks pushing back on Web Services in 2000 in favour of their old-school approaches. The package guys pushing back against SaaS or now the BI guys pushing back against the new wave of BI technologies and approaches the message is always the same:
We are happy doing what we are doing,
I can smell a change coming, the last few years have seen cloud and SaaS on the rise and seen a fragmentation in application development (thanks in a large part to the appalling stewardship of Java) and a real focus of budgets around BI and 'vanilla' package approaches. Now this is a good thing, both because I jumped out of the Java boat onto the BI boat a few years ago but also because its
Is your data science providing you enough indications that challenge your existing compensation strategy? Does it reveal that the art of compensation distribution performed by your managers is not in accordance with your compensation strategy? Old habits die-hard, so you need to make sure that your plan for data-driven decision-making is not getting overridden by compensation managers’ belief system and they are not ignoring data science recommendations.
Even today challenge is to effectively distribute (more...)
I’m wearing a Nike Fuelband – one of those fitness/activity tracker gizmos. Nike is offering both a website and an app showing my daily activity. As a customer, I am expecting these two to contain the same data. After all, my bank balance is the same in my mobile banking app, in an ATM or in a web browser.
Unfortunately, Nike does not have a proper infrastructure behind their gadget, so the numbers do not (more...)
There is an interesting article on Forbes where Paul Sonderegger from Oracle is making the case that you have to jump onto the “Big Data” bandwagon without delay if you want to avoid your big-data-using competitors crushing you.
But he would say that, wouldn’t he?
In reality, most companies already (more...)
The Oracle guys running the Big Data 4 the Enterprise Meetup
are always apologetic about marketing. The novelty is quite amusing. They do this because most Big Data Meetups are full of brash young people from small start-ups who use cool open source software. They choose cool open source software (more...)
On his recent Forbes report, Greg Satell lays down 5 steps to get Big Data working in your business. The first four are very well captured, but it was the fifth that really caught my attention: “Adopt a Big Data Mindset“. This is exactly where I want to drill in (more...)