Wednesday, July 31, 2013

Gaining Dependability Across All Business Activities Requires Standard of Standards to Tame Dynamic Complexity, Says The Open Group CEO

Transcript of a BriefingsDirect podcast on the need to mitigate risk and compliance issues in a unpredictable world.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: The Open Group.

Dana Gardner: Hello, and welcome to a special BriefingsDirect Thought Leadership Interview series, coming to you in conjunction with The Open Group Conference on July 15, in Philadelphia.

Gardner
I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator throughout these discussions on enterprise transformation in the finance, government, and healthcare sector.

We're here now with the President and CEO of The Open Group, Allen Brown, to explore the increasingly essential role of standards, in an undependable, unpredictable world. [Disclosure: The Open Group is a sponsor of BriefingsDirect podcasts.]

Welcome back, Allen.

Allen Brown: It’s good to be here, Dana.

Gardner: What are the environmental variables that many companies are facing now as they try to improve their businesses and assess the level of risk and difficulty? It seems like so many moving targets.

Brown: Absolutely. There are a lot of moving targets. We're looking at a situation where organizations are having to put in increasingly complex systems. They're expected to make them highly available, highly safe, highly secure, and to do so faster and cheaper. That’s kind of tough.

Gardner: One of the ways that organizations have been working toward a solution is to have a standardized approach, perhaps some methodologies, because if all the different elements of their business approach this in a different way, we don’t get too far too quickly, and it can actually be more expensive.

Perhaps you could paint for us the vision of an organization like The Open Group in terms of helping organizations standardize and be a little bit more thoughtful and proactive toward these changed elements?

Brown
Brown: With the vision of The Open Group, the headline is "Boundaryless Information Flow." That was established back in 2002, at a time when organizations were breaking down the stovepipes or the silos within and between organizations and getting people to work together across functioning. They found, having done that, or having made some progress toward that, that the applications and systems were built for those silos. So how can we provide integrated information for all those people?

As we have moved forward, those boundaryless systems have become bigger and much more complex. Now, boundarylessness and complexity are giving everyone different types of challenges. Many of the forums or consortia that make up The Open Group are all tackling it from their own perspective, and it’s all coming together very well.

We have got something like the Future Airborne Capability Environment (FACE) Consortium, which is a managed consortium of The Open Group focused on federal aviation. In the federal aviation world they're dealing with issues like weapons systems.

New weapons

Over time, building similar weapons is going to be more expensive, inflation happens. But the changing nature of warfare is such that you've then got a situation where you’ve got to produce new weapons. You have to produce them quickly and you have to produce them inexpensively.

So how can we have standards that make for more plug and play? How can the avionics within a cockpit of whatever airborne vehicle be more interchangeable, so that they can be adapted more quickly and do things faster and at lower cost. After all, cost is a major pressure on government departments right now.

We've also got the challenges of the supply chain. Because of the pressure on costs, it’s critical that large, complex systems are developed using a global supply chain. It’s impossible to do it all domestically at a cost. Given that, countries around the world, including the US and China, are all concerned about what they're putting into their complex systems that may have tainted or malicious code or counterfeit products.

The Open Group Trusted Technology Forum (OTTF) provides a standard that ensures that, at each stage along the supply chain, we know that what’s going into the products is clean, the process is clean, and what goes to the next link in the chain is clean. And we're working on an accreditation program all along the way.

We're also in a world, which when we mention security, everyone is concerned about being attacked, whether it’s cybersecurity or other areas of security, and we've got to concern ourselves with all of those as we go along the way.
The big thing about large, complex systems is that they're large and complex. If something goes wrong, how can you fix it in a prescribed time scale?

Our Security Forum is looking at how we build those things out. The big thing about large, complex systems is that they're large and complex. If something goes wrong, how can you fix it in a prescribed time scale? How can you establish what went wrong quickly and how can you address it quickly?

If you've got large, complex systems that fail, it can mean human life, as it did with the BP oil disaster at Deepwater Horizon or with Space Shuttle Challenger. Or it could be financial. In many organizations, when something goes wrong, you end up giving away service.

An example that we might use is at a railway station where, if the barriers don’t work, the only solution may be to open them up and give free access. That could be expensive. And you can use that analogy for many other industries, but how can we avoid that human or financial cost in any of those things?

A couple of years after the Space Shuttle Challenger disaster, a number of criteria were laid down for making sure you had dependable systems, you could assess risk, and you could know that you would mitigate against it.

What The Open Group members are doing is looking at how you can get dependability and assuredness through different systems. Our Security Forum has done a couple of standards that have got a real bearing on this. One is called Dependency Modeling, and you can model out all of the dependencies that you have in any system.

Simple analogy

A very simple analogy is that if you are going on a road trip in a car, you’ve got to have a competent driver, have enough gas in the tank, know where you're going, have a map, all of those things.

What can go wrong? You can assess the risks. You may run out of gas or you may not know where you're going, but you can mitigate those risks, and you can also assign accountability. If the gas gauge is going down, it's the driver's accountability to check the gauge and make sure that more gas is put in.

We're trying to get that same sort of thinking through to these large complex systems. What you're looking at doing, as you develop or evolve large, complex systems, is to build in this accountability and build in understanding of the dependencies, understanding of the assurance cases that you need, and having these ways of identifying anomalies early, preventing anything from failing. If it does fail, you want to minimize the stoppage and, at the same time, minimize the cost and the impact, and more importantly, making sure that that failure never happens again in that system.

The Security Forum has done the Dependency Modeling standard. They have also provided us with the Risk Taxonomy. That's a separate standard that helps us analyze risk and go through all of the different areas of risk.
You can't just dictate that someone is accountable. You have to have a negotiation.

Now, the Real-time & Embedded Systems Forum  has produced the Dependability through Assuredness, a standard of The Open Group, that brings all of these things together. We've had a wonderful international endeavor on this, bringing a lot of work from Japan, working with the folks in the US and other parts of the world. It's been a unique activity.

Dependability through Assuredness depends upon having two interlocked cycles. The first is a Change Management Cycle that says that, as you look at requirements, you build out the dependencies, you build out the assurance cases for those dependencies, and you update the architecture. Everything has to start with architecture now.

You build in accountability, and accountability, importantly, has to be accepted. You can't just dictate that someone is accountable. You have to have a negotiation. Then, through ordinary operation, you assess whether there are anomalies that can be detected and fix those anomalies by new requirements that lead to new dependabilities, new assurance cases, new architecture and so on.

The other cycle that’s critical in this, though, is the Failure Response Cycle. If there is a perceived failure or an actual failure, there is understanding of the cause, prevention of it ever happening again, and repair. That goes through the Change Accommodation Cycle as well, to make sure that we update the requirements, the assurance cases, the dependability, the architecture, and the accountability.

So the plan is that with a dependable system through that assuredness, we can manage these large, complex systems much more easily.

Gardner: Allen, many of The Open Group activities have been focused at the enterprise architect or business architect levels. Also with these risk and security issues, you're focusing at chief information security officers or governance, risk, and compliance (GRC), officials or administrators. It sounds as if the Dependability through Assuredness standard shoots a little higher. Is this something a board-level mentality or leadership should be thinking about, and is this something that reports to them?

Board-level issue

Brown: In an organization, risk is a board-level issue, security has become a board-level issue, and so has organization design and architecture. They're all up at that level. It's a matter of the fiscal responsibility of the board to make sure that the organization is sustainable, and to make sure that they've taken the right actions to protect their organization in the future, in the event of an attack or a failure in their activities.

The risks to an organization are financial and reputation, and those risks can be very real. So, yes, they should be up there. Interestingly, when we're looking at areas like business architecture, sometimes that might be part of the IT function, but very often now we're seeing as reporting through the business lines. Even in governments around the world, the business architects are very often reporting up to business heads.

Gardner: Here in Philadelphia, you're focused on some industry verticals, finance, government, health. We had a very interesting presentation this morning by Dr. David Nash, who is the Dean of the Jefferson School of Population Health, and he had some very interesting insights about what's going on in the United States vis-à-vis public policy and healthcare.

One of the things that jumped out at me was, at the end of his presentation, he was saying how important it was to have behavior modification as an element of not only individuals taking better care of themselves, but also how hospitals, providers, and even payers relate across those boundaries of their organization.
One of the things about The Open Group standards is that they're pragmatic and practical standards.

That brings me back to this notion that these standards are very powerful and useful, but without getting people to change, they don't have the impact that they should. So is there an element that you've learned and that perhaps we can borrow from Dr. Nash in terms of applying methods that actually provoke change, rather than react to change?

Brown: Yes, change is a challenge for many people. Getting people to change is like taking a horse to water, but will it drink? We've got to find methods of doing that.

One of the things about The Open Group standards is that they're pragmatic and practical standards. We've seen' in many of our standards' that where they apply to product or service, there is a procurement pull through. So the FACE Consortium, for example, a $30 billion procurement means that this is real and true.

In the case of healthcare, Dr. Nash was talking about the need for boundaryless information sharing across the organizations. This is a major change and it's a change to the culture of the organizations that are involved. It's also a change to the consumer, the patient, and the patient advocates.

All of those will change over time. Some of that will be social change, where the change is expected and it's a social norm. Some of that change will change as people, generations develop. The younger generations are more comfortable with authority that they perceive with the healthcare professionals, and also of modifying the behavior of the professionals.

The great thing about the healthcare service very often is that we have professionals who want to do a number of things. They want to improve the lives of their patients, and they also want to be able to do more with less.

Already a need

There's already a need. If you want to make any change, you have to create a need, but in the healthcare, there is already a pent-up need that people see that they want to change. We can provide them with the tools and the standards that enable it to do that, and standards are critically important, because you are using the same language across everyone.

It's much easier for people to apply the same standards if they are using the same language, and you get a multiplier effect on the rate of change that you can achieve by using those standards. But I believe that there is this pent-up demand. The need for change is there. If we can provide them with the appropriate usable standards, they will benefit more rapidly.

Gardner: Of course, measuring the progress with the standards approach helps as well. We can determine where we are along the path as either improvements are happening or not happening. It gives you a common way of measuring.

The other thing that was fascinating to me with Dr. Nash's discussion was that he was almost imploring the IT people in the crowd to come to the rescue. He's looking for a cavalry and he’d really seemed to feel that IT, the data, the applications, the sharing, the collaboration, and what can happen across various networks, all need to be brought into this.
Each department and each organization has its different culture, and bringing them together is a significant challenge.

How do we bring these worlds together? There is this policy, healthcare and population statisticians are doing great academic work, and then there is the whole IT world. Is this something that The Open Group can do -- bridge these large, seemingly unrelated worlds?

Brown: At the moment, we have the capability of providing the tools for them to do that and the processes for them to do that. Healthcare is a very complex world with the administrators and the healthcare professionals. You have different grades of those in different places. Each department and each organization has its different culture, and bringing them together is a significant challenge.

In some of that processes, certainly, you start with understanding what it is you're trying to address. You start with what are the pain points, what are the challenges, what are the blockages, and how can we overcome those blockages? It's a way of bringing people together in workshops. TOGAF, a standard of The Open Group, has the business scenario method, bringing people together, building business scenarios, and understanding what people's pain points are.

As long as we can then follow through with the solutions and not disappoint people, there is the opportunity for doing that. The reality is that you have to do that in small areas at a time. We're not going to take the entire population of the United States and get everyone in the workshop and work altogether.

But you can start in pockets and then generate evangelists, proof points, and successful case studies. The work will then start emanating out to all other areas.

Gardner: It seems too that, with a heightened focus on vertical industries, there are lessons that could be learned in one vertical industry and perhaps applied to another. That also came out in some of the discussions around big data here at the conference. The financial industry recognized the crucial role that data plays, made investments, and brought the constituencies of domain expertise in finance with the IT domain expertise in data and analysis, and came up with some very impressive results.

Do you see that what has been the case in something like finance is now making its way to healthcare? Is this an enterprise or business architect role that opens up more opportunity for those individuals as business and/or enterprise architects in healthcare? Why don't we see more enterprise architects in healthcare?

Good folks

Brown: I don't know. We haven't run the numbers to see how many there are. There are some very competent enterprise architects within the healthcare industry around the world. We've got some good folks there.

The focus of The Open Group for the last couple of decades or so has always been on horizontal standards, standards that are applicable to any industry. Our focus is always about pragmatic standards that can be implemented and touched and felt by end-user consumer organizations.

Now, we're seeing how we can make those even more pragmatic and relevant by addressing the verticals, but we're not going to lose the horizontal focus. We'll be looking at what lessons can be learned and what we can build on. Big data is a great example of the fact that the same kind of approach of gathering the data from different sources, whatever that is, and for mixing it up and being able to analyze it, can be applied anywhere.

The challenge with that, of course, is being able to capture it, store it, analyze it, and make some sense of it. You need the resources, the storage, and the capability of actually doing that. It's not just a case of, "I'll go and get some big data today."
The focus of The Open Group for the last couple of decades or so has always been on horizontal standards, standards that are applicable to any industry.

I do believe that there are lessons learned that we can move from one industry to another. I also believe that, since some geographic areas and some countries are ahead of others, there's also a cascading of knowledge and capability around the world in a given time scale as well.

Gardner: Well great. I'm afraid we'll have to leave it there. We've been talking about the increasingly essential role of standards in a complex world, where risk and dependability become even more essential. We have seen how The Open Group is evolving to meet these challenges through many of its activities and through many of the discussions here at the conference.

This special BriefingsDirect discussion comes to you in conjunction with The Open Group Conference 2013 in Philadelphia, and it is focused on Enterprise Transformation in the Finance, Government, and Healthcare sectors.

Please join me now in thanking our guest, Allen Brown, President and CEO of The Open Group. Thank you.

Brown: Thanks for taking the time to talk to us, Dana.

Gardner: This is Dana Gardner, Principal Analyst at Interarbor Solutions, your host and moderator through these thought leadership interviews. Thanks again for listening, and come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: The Open Group.

Transcript of a BriefingsDirect podcast on the need to mitigate risk and compliance issues in an unpredictable world. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.

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Monday, July 22, 2013

HP Vertica Architecture Gives Massive Performance Boost to Toughest BI Queries for Infinity Insurance

Transcript of a BriefingsDirect podcast on how a major insurance company is using improved data architecture to gain a competitive advantage.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Dana Gardner: Hello, and welcome to the next edition of the HP Discover Performance Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your moderator for this ongoing discussion of IT innovation and how it’s making an impact on people’s lives.

Gardner
Once again, we're focusing on how IT leaders are improving their services' performance to deliver better experiences and payoffs for businesses and end users alike, and this time we're coming to you directly from the HP Discover 2013 Conference in Las Vegas.

Our next innovation case study interview highlights how Infinity Insurance Companies in Birmingham, Alabama has been deploying a new data architecture to improve productivity for their analysis and business intelligence (BI). [Learn more about the upcoming Vertica conference in Boston Aug. 5.]

To learn more about how they are improving their performance and their results for their business activities, please join me in welcoming our guest, Barry Ralston, Assistant Vice President for Data Management at Infinity Insurance Companies. Welcome, Barry. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Barry Ralston: Thanks for having me, Dana.

Gardner: You're welcome. Tell me a bit about the need for change. What was it that you've been doing with your BI and data warehousing that prompted you to seek an alternative?

Ralston: Like many companies in our space, we have constructed an enterprise data warehouse deployed to a row-store technology. In our case, it was initially Oracle RAC and then, eventually, the Oracle Exadata engineered hardware/software appliance.

Ralston
We were noticing that analysis that typically occurs in our space wasn’t really optimized for execution via that row store. Based on my experience with Vertica, we did a proof of concept with a couple of other alternative and analytic store-type databases. We specifically chose Vertica to achieve higher productivity and to allow us to focus on optimizing queries and extracting value out of the data.

Gardner: Before we learn more about how that’s worked out for you, maybe you could explain for our listeners’ benefit, what Infinity Insurance Companies does. How big are you, and how important is data and analysis to you?

Ralston: We are billion-dollar property and casualty company, headquartered in Birmingham, Alabama. Like any insurance carrier, data is key to what we do. But one of the things that drew me to Infinity, after years of being in a consulting role, was the idea of their determination to use data as a strategic weapon, not just IT as a whole, but data specifically within that larger IT as a strategic or competitive advantage.

Vertica environment

Gardner: You have quite a bit of internal and structured data. Tell me a bit what happened when you moved into a Vertica environment, first to the proof of concept and then into production?

Ralston: For the proof of concept, we took the most difficult or worst-performing queries from our Exadata implementation and moved that entire enterprise data warehouse set into a Vertica deployment on three Dual Hex Core, DL380 type machines. We're running at the same scale, with the same data, with the same queries.

We took the top 12 worst-performing queries or longest-running queries from the Exadata implementation, and not one of the proof of concept queries ran less than 100 times faster. It was an easy decision to make in terms of the analytic workload, versus trying to use the row-store technology that Oracle has been based on.

Gardner: Let’s dig into that a bit. I'm not a computer scientist and I don’t claim to fully understand the difference between row store, relational, and the column-based approach for Vertica. Give us the quick "Data Architecture 101" explanation of why this improvement is so impressive? [Learn more about the upcoming Vertica conference in Boston Aug. 5.]

Ralston: The original family of relational databases -- the current big three are  Oracle, SQL Server and DB2 -- are based on what we call row-storage technologies. They store information in blocks on disks, writing an entire row at a time.

If you had a record for an insured, you might have the insured's name, the date the policy went into effect, the date the policy next shows a payment, etc. All those attributes were written all at the same time in series to a row, which is combined into a block.
It’s an optimal way of storing data for transaction processing.

So storage has to be allocated in a particular fashion, to facilitate things like updates. It’s an optimal way of storing data for transaction processing. For now, it’s probably the state-of-the-art for that. If I am running an accounting system or a quote system, that’s the way to go.

Analytic queries are fundamentally different than transaction-processing queries. Think of the transaction processing as a cash register. You ring up a sale with a series of line items. Those get written to that row store database and that works well.

But when I want to know the top 10 products sold to my most profitable 20 percent of customers in a certain set of regions in the country, those set-based queries don’t perform well without major indexing. Often, that relates back to additional physical storage in a row-storage architecture.

Column store databases -- Vertica is a native column store database -- store data fundamentally differently than those row stores. We might break down a record into an entire set of columns or store distinctly. This allows me to do a couple of different things from an architectural level.

Sort, compress, organize

First and foremost, I can sort, compress, and organize the data on disk much more efficiently. Compression has been recently added to row-storage architectures, but in a row-storage database, you largely have to compress at the entirety of a row.

I can’t choose an optimal compression algorithm for just a date, because in that row, I will have text, numbers, and dates. In a column store, I can apply specific compression algorithm to the data that's in that column. So date gets one algorithm, a monotone increasing key like a surrogate key you might have in a dimensional data warehouse, has a different encoding algorithm, etc.

This is sorting. How data gets retrieved is fundamentally different, another big point for row-storage databases at query time. I could say, "Tell me all the customers that bought a product in California, but I only want to know their last name."

If I have 20 different attributes, a row-storage database actually has to read all the attributes off of disk. The query engine eliminates the ones I didn’t ask for in the eventual results, but I've already incurred the penalty of the input-output (I/O). This has a huge impact when you think of things like call detail records in telecom which have a 144-some odd columns.

If I'm only asking against a column store database, "Give me all the people who have last names, who bought a product in California," I'm essentially asking the database to read two columns off disk, and that’s all that’s happening. My I/O factors are improved by an order of 10 or in the case of the CDR, 1 in 144.
The great question is what ends up being the business value.

Gardner: Fundamentally it’s the architecture that’s different. You can’t just go back and increase your I/O improvements in those relational environments by making it in-memory or cutting down on the distance between the data and the processing. That only gets you so far, and you can only throw hardware at it so much. Fundamentally, it’s about the architecture.

Ralston: Absolutely correct. You've seen a lot of these -- I think one of the fun terms around this is "unnatural acts with data," as to how data gets either scattered or put into a cache or other things. Every time you introduce one of these mechanisms, you're putting another bottleneck between near real-time analytics and getting the data from a source system into a user’s hands for analytics. Think of a cache. If you’re going to cache, you’ve got to warm that cache up to get an effect.

If I'm streaming data in from a sensor, real-time location servers, or something like that, I don’t get a whole lot of value out of the cache to start until it gets warmed up. I totally agree with your point there, Dana, that it’s all about the architecture.

Gardner: So you’ve gained on speed and scale, and you're able to do things you couldn’t do differently when it comes to certain types of data. That’s all well and good for us folks who are interested in computers. What about the people who are interested in insurance? What were you able to bring back to your company that made a difference for them and their daily business that’s now allowed you to move beyond your proof of concept into wider production?

Ralston: The great question is what ends up being the business value. In short, leveraging Vertica, the underlying architecture allows me to create a playfield, if you will, for business analysts. They don’t necessarily have to be data scientists to enjoy it and be able to relate things that have a business relationship between each other, but not necessarily one that’s reflected in the data model, for whatever reason.

Performance suffers

Obviously in a row storage architecture, and specifically within dimensional data warehouses, if there is no index between a pair of columns, your performance begins to suffer. Vertica creates no indexes and it’s self-indexing the data via sorting and encoding.

So if I have an end user who wants to analyze something that’s never been analyzed before, but has a semantic relationship between those items, I don’t have to re-architect the data storage for them to get information back at the speed of their decision.

Gardner: You've been able to apply the Vertica implementation to some of your existing queries and you’ve gotten some great productivity benefits from that. What about opening this up to some new types of data and/or giving your users the folks in the insurance company the opportunity to look to external types of queries and learn more about markets, where they can apply new insurance products and grow the bottom line rather than just repay cowpaths?

Ralston: That's definitely part of our strategic plan. Right now, 100 percent of the data being leveraged at Infinity is structured. We're leveraging Vertica to manage all that structured data, but we have a plan to leverage Hadoop and the Vertica Hadoop connectors, based on what I'm seeing around HAVEn, the idea of being able to seamlessly structured, non-structured data from one point.
Then, I’ve delivered what my CIO is asking me in terms of data as a competitive advantage.

Insurance is an interesting business in that, as my product and pricing people look for the next great indicator of risk, we essentially get to ride a wave of that competitive advantage for as long a period of time as it takes us to report that new rate to a state. The state shares that with our competitors, and then our competitors have to see if they want to bake into their systems what we’ve just found.

So we can use Vertica as a competitive hammer, Vertica plus Hadoop to do things that our competitors aren’t able to do. Then, I’ve delivered what my CIO is asking me in terms of data as a competitive advantage.

Gardner: Well, great. I'm afraid we will have to leave it there. We've been learning about how Infinity Insurance Companies has been deploying HP Vertica technology and gaining scale and speed benefits. And now also setting themselves up for perhaps doing types of queries that they hadn’t been able to do before.

I’d like to thank our guest for joining us, Barry Ralston, Assistant Vice President for Data Management at Infinity Insurance company. Thank so much, Barry. [Learn more about the upcoming Vertica conference in Boston Aug. 5.]

Ralston: Thank you very much.

Gardner: I’d like to thank our audience as well for joining us for this special HP Discover Performance Podcast, coming to you from the HP Discover 2013 Conference in Las Vegas.

I'm Dana Gardner, Principle Analyst at Interarbor Solutions, your host for this ongoing series of HP-sponsored discussions. Thanks again for listening, and come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Transcript of a BriefingsDirect podcast on how a major insurance company is using improved data architecture to gain a competitive advantage. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.

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