Data isn't really respected in businesses, you can see that because unlike other corporate assets there is rarely a decent corporate catalog that shows what exists and who has it. In the vast majority of companies there is more effort and automation put into tracking laptops than there is into cataloging and curating information.
Historically we've sort of been able to get away with this
Over six parts I've gone through a bit of a journey on what Big Data Security is all about.
Securing Big Data is about layers
Use the power of Big Data to secure Big Data
How maths and machine learning helps
Why its how you alert that matters
Why Information Security is part of Information Governance
Classifying Risk and the importance of Meta-Data
The fundamental point here is that
So now your Information Governance groups consider Information Security to be important you have to then think about how they should be classifying the risk. Now there are docs out there on some of these which talk about frameworks. British Columbia's government has one for instance that talks about High, Medium and Low risk, but for me that really misses the point and over simplifies the
What does your security team look like today?
Or the IT equivalent, "the folks that say no". The point is that in most companies information security isn't actually something that is considered important. How do I know this? Well because basically most IT Security teams are the equivalent of the nightclub bouncers, they aren't the people who own the club, they aren't as important as the
In the first three parts of this I talked about how Securing Big Data is about layers, and then about how you need to use the power of Big Data to secure Big Data, then how maths and machine learning helps to identify what is reasonable and was is anomalous.
The Target Credit Card hack highlights this problem. Alerts were made, lights did flash. The problem was that so many lights flashed and
In the first two parts of this I talked about how Securing Big Data is about layers, and then about how you need to use the power of Big Data to secure Big Data. The next part is "what do you do with all that data?". This is where Machine Learning and Mathematics comes in, in other words its about how you use Big Data analytics to secure Big Data.
What you want (more...)
In the first part of Securing Big Data I talked about the two different types of security. The traditional IT and ACL security that needs to be done to match traditional solutions with an RDBMS but that is pretty much where those systems stop in terms of security which means they don't address the real threats out there, which are to do with cyber attacks and social engineering. An ACL is only
As Big Data and its technologies such as Hadoop head deeper into the enterprise so questions around compliance and security rear their heads.
The first interesting point in this is that it shows the approach to security that many of the Silicon Valley companies that use Hadoop at scale have taken, namely pretty little really. It isn't that protecting information has been seen as a massively
I’m taking a few weeks defocused from work, as a kind of grandpaternity leave. That said, the venue for my Dances of Infant Calming is a small-but-nice apartment in San Francisco, so a certain amount of thinking about tech industries is inevitable. I even found time last Tuesday to meet or speak with my clients at WibiData, MemSQL, Cloudera, Citus Data, and MongoDB. And thus:
1. I’ve been sloppy in my terminology around “geo-distribution”, in (more...)
In the past 2 years, I have met many developers, architects that are working on “big data” projects. This sounds amazing, but quite often the truth is not that amazing.
You believe that you have a big data project?
Do not start with the installation of an Hadoop Cluster -- the "how"
Start to talk to business people to understand their problem -- the "why"
Understand the data you must
I’ve talked with many companies recently that believe they are:
- Focused on building a great data management and analytic stack for log management …
- … unlike all the other companies that might be saying the same thing …
- … and certainly unlike expensive, poorly-scalable Splunk …
- … and also unlike less-focused vendors of analytic RDBMS (which are also expensive) and/or Hadoop distributions.
At best, I think such competitive claims are overwrought. Still, it’s a genuinely (more...)
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...)
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...)