Six things to make your Big Data project succeed

So I wrote about why your Hadoop project will fail so I think its only right that I should follow up with some things that you can do to actually make the Big Data project you take on succeed.  The first thing you need to do is stop trying to make 'Big Data' succeed and instead start focusing on how you educate the business on the value of information and then work out how to deliver new value... that just so happens to be delivered with Big or Fast Data technologies

Don't try and change the business
The first thing is to stop trying to see technology as being a goal in itself and complaining when the business doesn't recognise that your 'magic' technology is the most important thing in the world.  So find out how the business works, look at how people actually work day to day and see how you can improve that.

Sounds simple?  Well the good news is that it is, but it means you need to forget about technology until you know how the business works.

Explain why Information Matters
The next bit after you've understood the business better is to explain to them why they should care about information.  Digitization is the buzzword you need to learn, folks like MIT Sloan (Customer Facing Digitization), Harvard Business Review (are you ready for Digitization?) and Davos (Digitization and Growth) are saying that this is the way forwards.  And what is Digitization? In the raw its just about converting stuff into digital formats, but the reality is that what its about is having an information and analytical driven business.  The prediction of all the business schools is that companies that do this will out perform their competition.

This is an important step, its about shifting Information from being a technology and IT conversation towards the business genuinely seeing information as a critical part of business growth.  Its also about you as an IT professional learning how to communicate technology changes in the language the business wants to hear.  They don't want to hear 'Hadoop' they want to hear 'Digitization'.

Find a problem that needs a new solution
The next key thing is finding a problem that isn't well served by your current environments.  If you could solve a problem by just having a new report on an EDW then it really doesn't prove anything to use new technologies to do that in a more time consuming way.  The good news is there are probably loads of problems out there not well served by your current environments.  From volume challenges around sensor data, click stream through to real-time analytics, predictive analytics through data discovery and ad-hoc information solutions there are lots of business problems.

Find that problem, find the person or group in the business that cares about having that problem solves and be clear about what the benefits of solving that problem are.

Get people with the 'scars and ribbons'
What do I do when I work with a new technology?  Two things, firstly I get some training and from that build something for myself that helps me learn.  If I'm doing it at work in building a business I then go and find someone who has already done this before and hire them or transfer them into my team.

Bill Joy once said that the smartest people weren't at Sun so they should learn from outside.  I'm not Bill Joy, you aren't Bill Joy, so we can certainly learn from outside.  Whether this means going to a consultancy who has done it before, hiring people in who have done it before doesn't really matter.  The point is that unless you really are revolutionising the IT market you are doing something that someone has done before, so your best bet is to learn from their example.

It stuns me how many people embark on complex IT projects having never used the technology before and are then surprised that the project fails.  Get people with the 'scars and ribbons' who can tell you what not to do which is massively more important than what to do.

Throw out some of your old Data Warehouse thinking
The next bit is something that you need to forget, a cherished truth that no longer holds.  Get rid of the notion that your job as a data architect is to dictate a single view to the business.  Get rid of the thought that the cherished ETL process.  Land the data in Hadoop, all the data you can, don't worry if you don't think you might not use it, you are landing it Hadoop and then turning into the views or analytics.  There is no benefit in not taking everything across and lots of benefits for doing so.

In other words you've got the problem, that is the goal, now go and collect all the data but not worry about the full A-Z straight away by defining Z and working backwards.  Understand the data areas, drop that into Hadoop and then worry about what the right A-Z is today knowing that if its a different route tomorrow you've got the data ready to go without updating the integration.

Then if you have another problem that needs access to the same data don't automatically try and make one solution do two things.  Its perfectly ok to create a second solution to solve that problem on top of Hadoop.  You don't need everyone to agree on a single schema, you just need to be able to solve the problem.  The point here is that to get different end-results you need to start thinking differently.

Don't get hung up on NoSQL, don't get hung up on Hadoop
The final thing is the dirty secret of the Hadoop world that has rapidly become the bold proclamation - NoSQL really isn't for everyone and SQL is perfectly good for lots of cases.  Hive, Impala, HAWQ are all addressing exactly that challenge, and you shouldn't limit yourself to Hadoop friendly approaches, if the right way is to push it to your existing data warehouse from Hadoop... do it.  If the requirement is to have some fast data processing then do that.

The point here is your goal is to show how the new technologies are more flexible and better able to adapt to the business and how the new IT approach is to match what the business wants not to try and force an EDW onto it every time.


The point here is that making your Big Data program succeed is actually about having the business care about the value that information brings and then fitting your approach to match what the business wants to achieve.

The business is your customer, time do do what they want, not force an EDW down their throats.

The People's Democratic Republic of IT

IT is a communist state in many organisations, one that believes in rigid adherence to inflexible approaches despite clear indications that they inhibit growth and a central approach to planning that Mao and Stalin would have thought is taking things a little too far. This really doesn't make sense in the capitalistic world of business and the counter-revolution is well under way. Its

I don't think the word 'Enterprise' is really worth anything in terms of something being a single standard Enterprise approach.  Whether that is Enterprise Resource Planning, Enterprise Data Warehouse, Enterprise Service Bus or Enterprise Architecture you either end up with multiple solutions or a central solution that isn't used to the level it was envisaged so you get lots of solutions on the side.

Part of this is because in the capitalistic world of business it appears that communist style central planning has been, and remains, the normal approach.  This People's Democratic Republic of IT approach has two key parts to it

1. IT knows best and will give everyone 'each according to their needs' and decide what those needs are.
2. Cultish following of other communist plans, independent of whether the users want them.

The world of integration is a great example of the latter.  Do you know how much the business cares about whether you integrate two systems using REST, SOAP,sockets or flying monkeys?  ZERO.  Hell probably even less than zero in that they have an active disinterest in it.  Yet in IT we don't take this as a guidance of 'its not important, lets commoditise the fuck out of it'.  Nope we continue to 'innovate' where it really doesn't matter and we do so because a whole heap of hype tells us to... business hype?  Of course not, its hype from people who think they've discovered the universal hammer that turns everything into a nail.

On the former its the realm of 'Enterprise Architecture' and EDWs that really underline just how much IT often resembles the politburo.  Here groups of worthy individuals set about on the business equivalent of the Cultural Revolution or Stalin's grand plan for agriculture.  They just know that if everyone would just work in the same way then everything would be so much better.  So off they trot pushing a single solution and historically this was pushed all the way through to production and the business went:

"Well its not what I wanted but its a bit less shit than what I've got"

So IT created grand strategic plans (and I've said before there is no such thing as IT strategy) often in areas that the business really didn't care and off the business went and started using DropBox, salesforce.com and Amazon.

In effect the Shadow IT efforts of the business are analogous to the black market economies that often thrived in communist countries in the 80s.  Getting on doing what they need to do and being a lot more efficient than the state in doing it.  What we are seeing today is that as budget shift more and more towards the business the shadow IT market is getting bigger and bigger and the central planning has suddenly hit an issue.

The business understands technology

 Maybe not in the depth that IT does, but what the business understands is a bit more valuable

They understand how to focus on outcomes that add value, not technology hype.

So now as the Enterprise Architect says "you cannot do that, it is against our policy" the business says "stuff that for a game of soldiers, your policy doesn't work for us.".  The business is having its Berlin Wall moment, and while the IT communist state, the People's Democratic Republic of IT (because communist states love claiming they are democratic) might hold on for a while the reality is that the world is beginning to come crashing down.

Its time for IT to embrace capitalism, embrace value over technology and outcomes over acronyms.

How integration guys created a data security nightmare

There has been a policy in integration that has stored up a really great challenge of data security, and by great I don't mean 'fantastic' I mean 'aw crap'.  Its a policy that was done for the best of reasons and one that really will in future represent a growing challenge to Big Data and federated information.

The policy can be described as this:

Users authenticate with Apps, Apps authenticate with the database and Apps authenticate with the ESB/EAI/Integration

What this means is that Users don't authenticate against any of the federated data.  This is normally glossed over by saying that 'the source application is responsible for filtering' but the reality is that applications rarely do this terribly well.  Put it this way, most of the time when a front end banking system accessing your account information the only reason its getting your account data is because of the account ID it has, if it for some reason had the wrong account ID stored then it would display something else even though that information isn't yours.

This approach has tended to work for operational systems however because they work in linear ways on data sets, you know what you are showing and you pull out what you want to show.  The trouble is as these federated sets are then shifted into next generation Big Data solutions or accessed in a federated query is that the security model completely breaks down because application to application security doesn't recognise the individual actually making the request.

So now we have a world where the data sources don't do data security and privacy 'by design' they do it 'by functionality'.  So the reason you get your account information is because of that magic ID, but there is nothing stopping a piece of code saying 'return account information from account ID, account ID +1 and account ID +3. Its just practice that stops that rather than a fundamental information security approach.

There are mechanisms that can help with this but historically they've been more pain than its worth.  Its going to be interesting seeing how the next generation of joined up analytics and operational IT estates will retrofit user and role level analytical security into a world of application to application authentication.

Six reasons your Big Data Hadoop project will fail in 2014

Ok so Hadoop is the bomb, Hadoop is the schizzle, Hadoop is here to solve world hunger and all problems.  Now I've talked before about some of the challenges around Hadoop for enterprises but here are six reasons that Information Week is right when it says that Hadoop projects are going to fail more often than not.

1. Hadoop is a Java thing not a BI thing
The first is the most important challenge, I'm a Java guy, I'm a Java guy who thinks that Java has been driven off a cliff by its leadership in the last 8 years but its still one of the best platforms out there.  However the problems that Hadoop is trying to address are analytics problems, BI problems.  Put briefly BI guys don't like Java guys and Java guys don't like BI guys.  For Java guys Hadoop is yet more proof that they can do everything, but BI guys know that custom build isn't an efficient route to deliver all of those BI requirements.

On top of that the business folks know SQL, often they really know SQL, SQL is the official language of business and data.  So a straight 'No-SQL' approach is doomed to fail as you are speaking French to the British.  2014 will be the year when SQL on Hadoop becomes the norm but you are still going to need your Java and BI guys to get along, and you are going to have to recognise that SQL beats No-SQL.

2. You decide to roll-your own
Hadoop is open source, all you have to do is download it, install it and off you go right?  There are so many cases of people not doing that right that there is an actual page explaining why they won't accept those as bugs.  Hadoop is a bugger to install, it requires you to really understand how distributed computing works, and guess what?  You thought you did but it turns out you really didn't.  Distributed computing and multi-threaded computing are hard.

There are three companies you need to talk to Pivotal, Cloudera and Hortonworks and how easy can they make it? Well Pivotal have an easy Pivotal HD Hadoop Virtual Machine to get you started and even claim that that they can get you running a Hadoop cluster in 45 minutes.

3. You are building a technical proof of concept... why?
One reason that your efforts will fail is that you are doing a 'technical proof of concept' at the end of which you will amazingly find that something used in some of the biggest analytics challenges on planet earth at the likes of Yahoo fits your much, much smaller challenge.  Well done, you've spent money proving the obvious.

Now what?  How about solving an actual business problem?  Actually why didn't you start by solving an actual business problem as a way to see how it would work for what the business faces?  Technical proof of concepts are pointless, you need to demonstrate to the business how this new technology solve their problems in a better (cheaper, faster, etc) way.

4. You didn't understand what Hadoop was bad at
Hadoop isn't brilliant at everything analytical... shocking eh?  So that complex analytics you want to do which is effectively a complex 25 table join and then do the analytics... yeah that really isn't going to work too well.  Those bits where you said that you could do that key business use case faster and cheaper and then it took 2 days to run?

Hadoop is good a some things, but its not good at everything.  That is why folks are investing in SQL technologies on top of Hadoop, some of which like Pivotal's HAWQ or Cloudera's Impala, with Pivotal already showing how the bridge between traditional MPP and Hadoop is going to be made.

5. You didn't understand that its part of the puzzle
One of the big reasons that Hadoop pieces fail to really deliver is that they are isolated silos, they might even be doing some good analytics but people can't see that analytics where they care about it.  Sure you've put up some nice web-pages for people but they don't use that in their daily lives.  They want to see the information pushed into the Data Warehouse so they can see it in their reports, they want it pushed to the ERP so they can make better decisions... they might want it in many many places but you've left it in the one place that they don't care about it.

When looking at the future of your information landscape you need to remember that Hadoop and NoSQL are just a new tool, a good new tool and one that has a critical part to play but its just one new tool in your toolbox.

6. You didn't change
The biggest reason that your Hadoop project will fail however is that you've not changed some of your basic assumptions and looked how Hadoop enables you to do things differently.  So you are still doing ETL to transform into some idealised schema which is based on a point in time view of what is required.  You are doing that into a Hadoop cluster which couldn't care less about redundant or unused data and where the costs of that are significantly lower than doing another set of ETL development.

You've carried on thinking about grand enterprise solutions to which everyone will come and be beholden to your technical genius.

What you've not done is sit back and think 'the current way sucks for the business can I change that?' because if you had you'd have realised that using Hadoop as a Data substrate/lake layer makes more sense than ETL and you'd have realised that its actually local solutions that get used the most not corporate ones.

Your Hadoop project will fail because of you
The main reason Hadoop projects will fail is because you approach using a new technology with an old mindset, you'll try and build a traditional BI solution in a traditional BI way and you'll not understand that Java doesn't work like that, you'll not understand how Map Reduce is different to SQL and you'll plough on regardless and blame the technology.

Guess what though?  The technology works at massive scale, much, much bigger than anything you've ever deployed.  Its not the technology, its you.

So what to do?
.... I think I'll leave that for another post

Why your IT strategy failed or why the business hates IT

One of the most depressing things in IT is our inability to learn.  From the 'Oh look our massive waterfall project ran over budget' to the 'I really can't maintain the code we wrote that doesn't have a design or documentation' we do the same things as an industry over and over again.  Most depressing however is the phrase 'The IT Strategy would work if the business would just change'.

To illustrate this I'd like to tell you a tale, the names will not be used to protect the guilty but it sums up nicely the lunacy of many IT strategy efforts.

Many moons ago I was working for the business side of a large and very successful company.  This company was seen as a genuine market leader and I was working on some very complex mathematics around predictive analytics that the business folks wanted to make their supply chain run better.  There were two highlights through the process from the IT department.

The first was when discussing how such a solution would be implemented and integrated into the operational systems.  IT had a strategy you see and by strategy I mean they had picked a couple of vendors, the solution I was working on had some very specific requirements and wasn't available from those vendors.  An Enterprise Architect from the IT department said in a pretty well attended meeting

'It doesn't matter what the business wants, if we say it isn't going in, it isn't going in.'

The project continued on however as the business saw value in it and wanted to understand what could be done.  One of the key pieces was that we'd need some changes in how operational processes worked, not big ones but more we'd change the way people worked within the existing processes by giving them better information.  To this end we had a workshop with the business and certain key IT folks and worked out how we'd have to design the interfaces and processes to work within the current business environment and culture.  It was a good workshop and the business folks were very happy.

Then came IT, IT you see had a big strategic project to replace all of the existing systems with 'best of breed' solutions.  I'd always assumed that given the massive budget for that program the business was fully engaged... then this happened....

One of the IT folks chirped up and said : "We need to have a workshop so we can tell you what your new operational processes are going to be"

Note the 'tell'... to which the most senior business guy there (a board member IIRC) said

"How do you mean tell us?"

IT Guy: "The new systems have new processes and we need to tell you what they are so you can change."

Business Guy:"Have you done an impact analysis against our current processes?"

IT Guy: "No we've just defined the Best Practice To-Be processes, you need to do the impact and change management.  We need the meeting so we can tell you what the To-Be processes are"

Business Guy in a voice so dripping with sarcasm I thought we'd have a flood: "I look forward to our IT department telling the business what Best Practice is for our industry."

IT Guy, completely failing to read the sarcasm: "Great we'll get it organised"

This is one of the most visible examples of my career on why IT strategies fail.  I've said before there is no such thing as IT strategy its the job of IT to help automate and improve the business strategy, that means thinking tactically and taking strategy from the business model.

"Culture eats strategy for breakfast"

This is the reality and an IT approach that seeks to drive over the culture and dictate from a position of technology purity will fail.  You can change the culture, its hard and its not a technology thing, but you always need to be aware of the culture in order to succeed.

IT Strategy, if such a thing exists, is there to make the business better not to make IT better.

Why in Business driven information its the consumers view that matters

When doing the Business Data Lake pieces it took me back to a view that I had around SOA in that you should take the consumers view when designing a service.  This I think is more critical when looking at analytics and reporting where it really is all about the consumption.

What does this mean though to think about data from the consumers perspective?  We've all had the '3 V's' shoved at us and mostly realised the one that counts in Big Data is actually value.  So taking a Business SOA look at data means that you need to think about the business view and crucially the business value to understand what this actually means.

To this I'd say there are three ways that you can measure whether something is business driven or not

1. The Natural View - is the view on information being presented one that is naturally understandable by a given part of the business
2. Value based cost - does the cost being charged reflect the value being delivered
3. Dynamic Performance - ramp-up, ramp-down as the demand requires

These come back to a mantra I used a lot back when I was talking about the true impact of SOA on an IT estate: Create an IT estate that looks like the business, evolves like the business and is costed based on the business value it delivers.

With SOA in the operational sense this meant having a clear Business Service Architecture and that thinking now applies to Data.  There is no difference between the business views and KPIs between the operational and post-transactional world, indeed the more that analytics becomes the difference in operations the less that difference can be tolerated.

The difference however is in how information is accessed.  In the operational world when you want information from another domain you request it on demand.  In the post transactional world however this is about providing access to the landed (stored) information from other areas in the context that a given domain wants to see it.  Its here that new technologies add value as they enable that distillation to be done into the right business context, indeed enabling the same information to be distilled by different business areas in the right way for their context.

This is the same as you do in the operational space, requesting information from another business service and then converting the result into what makes sense in your local context.

By having a single consistent model between both the operational and post-transactional world you make integrating analytics much easier as you are not requiring your consumers to mentally shift between an operational view and the local view.

So as with a business service architecture which represents the business model so now that business consumer view should be reflected in your analytical applications to create a single model for IT that spans both operations and analytics and now gives the business that local view, the natural view for them, of information.

Now to the other two pieces: Value based Cost and Dynamic Performance.  These two are linked as value is not something that is fixed over time, closing the books is something where high performance is justified at a quarter end or other accounting deadline, but having a high performance solution when not required is wasted cost.

Therefore the new generation of solutions are about Elastic Analytics, that is analytics which can adapt and change based on the business demand.  There needs to be an end to the 'I think I might need in memory so I'll put it all in-memory' or worse the 'Damn I had it all on disk and now I need in-memory'.

The future is about Analytics aligned to the business not aligned to an idealised IT view.