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
"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,
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...)
Yesterday's UKOUG Analytics event
was a mixture of presentations about OBIEE with sessions on the frontiers of data analysis. I'm not going to cover everything, just dipping into a few things which struck me during the day
During the day somebody described dashboards as "Fisher Price activity centres for managers". (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...)
Big Data – The New Information Before asking the crystal ball what can Big Data do for you, sit back and think about these four questions: Where’s the new information? Where could it be? If it was in the right place, what could happen? (Challenges of the main industries) What are the (more...)
Hello readers of my infrequent blog posts! I have started a new job, working on documentation for Cloudera, specifically for the Impala project, which is bringing fast interactive SQL to the Hadoop ecosystem. Read the Impala documentation. Download the Impala software. Get the QuickStart VM to play around with a (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.
Research: the heart that pumps data If you talk to any kid in school about how he acquires knowledge, he would say that is through studying. The study uses books, classes, internet resources, and all the classic means of knowledge gathering. The further school gets into science the more important it gets to gather knowledge [...]
The question is not anymore if you have a Big Data strategy, the challenge is how are you going to roll it out. What layers of your Information Systems will change? And most importantly: level up the expectations at all levels of the enterprise. Big Data at the Enterprise it’s not about hype and I [...]