Category Archives: Architects
Just last week, I visited a client for whom I had been consulting on-and-off for several years. On the meeting room wall, I saw their Enterprise Architecture portfolio, beautiful graphically designed and printed on a giant sheet of paper. My host proudly informed me how much she enjoyed putting that diagram together in 2009.
I jokingly reminded her of the famous notion of “art for art’s sake”; which is an appropriate phrase to describe what many architects are doing when populating frameworks. Indeed, when we refer to Enterprise Architecture, we must remember that the term ‘architecture’ is, itself, a metaphor.
In a tough economy, when competition is increasingly global and marketplaces are shifting, this ability to make tough decisions is going to be essential. Opportunities to save costs are going to be really valued, and architecture invariably helps companies save money. The ability to reuse, and thus rapidly seize the next related business opportunity, is also going to be highly valued.
The thing you have to be careful of is that if you see your markets disappearing, if your product is outdated, or your whole industry is redefining itself, as we have seen in things like media, you have to be ready to innovate. Architecture can restrict your innovative gene, by saying, “Wait, wait, wait. We want to slow down. We want to do things on our platform.” That can be very dangerous, if you are really facing disruptive technology or market changes.
Albert Camus wrote a famous essay exploring the Sisyphus myth called “The Myth of Sisyphus,” where he reinterpreted the central theme of the myth. Similarly, we need to challenge the myths of Enterprise Architecture and enterprise system/solution architecture in general – not meekly accept them.
IEEE says, “A key premise of this metaphor is that important decisions may be made early in system development in a manner similar to the early decision-making found in the development of civil architecture projects.”
Keep asking yourself, “When is what we built that’s stable actually constraining us too much? When is it preventing important innovation?” For many architects, that’s going to be tough, because you start to love the architecture, the standards, and the discipline. You love what you’ve created, but if it isn’t right for the market you’re facing, you have to be ready to let it go and go seize the next opportunity.
The central message is as follows: ‘documenting’ architecture in various layers of abstraction for the purposes of ‘completeness’ is plainly ridiculous. This is especially true when the effort to produce the artifacts takes such an amount of time as to make the whole collection obsolete on completion.
This got me thinking: What is the biggest bottleneck in the delivery of business value today? I know I look at things from a data perspective, but data is the biggest bottleneck. Consider this prediction from Gartner:
“Gartner predicts organizations will spend one-third more on app integration in 2016 than they did in 2013. What’s more, by 2018, more than half the cost of implementing new large systems will be spent on integration. “
When we talk about application integration, we’re talking about moving data, synchronizing data, cleansing, data, transforming data, testing data. The question for architects and senior management is this: Do you have the Data Foundation for Execution you need to drive the business results you require to compete? The answer, unfortunately, for most companies is; No.
All too often data management is an add-on to larger application-based projects. The result is unconnected and non-interoperable islands of data across the organization. That simply is not going to work in the coming competitive environment. Here are a couple of quick examples:
- Many companies are looking to compete on their use of analytics. That requires collecting, managing, and analyzing data from multiple internal and external sources.
- Many companies are focusing on a better customer experience to drive their business. This again requires data from many internal sources, plus social, mobile and location-based data to be effective.
When I talk to architects about the business risks of not having a shared data architecture, and common tools and practices for enterprise data management, they “get” the problem. So why aren’t they addressing it? The issue is that they find that they are only funded to do the project they are working on and are dealing with very demanding timeframe requirements. They have no funding or mandate to solve the larger enterprise data management problem, which is getting more complex and brittle with each new un-connected project or initiative that is added to the pile.
Studies such as “The Data Directive” by The Economist show that organizations that actively manage their data are more successful. But, if that is the desired future state, how do you get there?
Changing an organization to look at data as the fuel that drives strategy takes hard work and leadership. It also takes a strong enterprise data architecture vision and strategy. For fresh thinking on the subject of building a data foundation for execution, see “Think Data-First to Drive Business Value” from Informatica.
* By the way, Informatica is proud to announce that we are now a sponsor of the MIT Center for Information Systems Research.
Adrian gathered experts and built workgroups to dig into the issue and do root cause analysis. The workgroups came back with some pretty surprising results.
- Most people expected that “incorrect data” (missing, out of date, incomplete, or wrong data) would be the main problem. What they found was that this was only #5 on the list of issues.
- The #1 issue was “Too much data.” People working with the data could not find the data they needed because there was too much data available, and it was hard to figure out which was the data they needed.
- The #2 issue was that people did not know the meaning of data. And because people had different interpretations of the data, the often produced analyses with conflicting results. For example, “claims paid date” might mean the date the claim was approved, the date the check was cut or the date the check cleared. These different interpretations resulted in significantly different numbers.
- In third place was the difficulty in accessing the data. Their environment was a forest of interfaces, access methods and security policies. Some were documented and some not.
In one of the workgroups, a senior manager put the problem in a larger business context;
“Not being able to leverage the data correctly allows competitors to break ground in new areas before we do. Our data in my opinion is the ‘MOST’ important element for our organization.”
What started as a relatively straightforward data quality project became a more comprehensive enterprise data management initiative that could literally change the entire organization. By the project’s end, Adrian found himself leading the data strategy of the organization.
This kind of story is happening with increasing frequency across all industries as all businesses become more digital, the quantity and complexity of data grows, and the opportunities to offer differentiated services based on data grow. We are entering an era of data-fueled organizations where the competitive advantage will go to those who use their data ecosystem better than their competitors.
Gartner is predicting that we are entering an era of increased technology disruption. Organizations that focus on data as their competitive edge will have the advantage. It has become clear that a strong enterprise data architecture is central to the strategy of any industry-leading organization.
For more future-thinking on the subject of enterprise data management and data architecure see Think ‘Data First” to Drive Business Value
This creative thinking to solve a problem came from a request to build a soldier knife from the Swiss Army. In the end, the solution was all about getting the right tool for the right job in the right place. In many cases soldiers didn’t need industrial strength tools, all they really needed was a compact and lightweight tool to get the job at hand done quickly.
Putting this into perspective with today’s world of Data Integration, using enterprise-class data integration tools for the smaller data integration project is over kill and typically out of reach for the smaller organization. However, these smaller data integration projects are just as important as those larger enterprise projects, and they are often the innovation behind a new way of business thinking. The traditional hand-coding approach to addressing the smaller data integration project is not-scalable, not-repeatable and prone to human error, what’s needed is a compact, flexible and powerful off-the-shelf tool.
Thankfully, over a century after the world embraced the Swiss Army Knife, someone at Informatica was paying attention to revolutionary ideas. If you’ve not yet heard the news about the Informatica platform, a version called PowerCenter Express has been released and it is free of charge so you can use it to handle an assortment of what I’d characterize as high complexity / low volume data integration challenges and experience a subset of the Informatica platform for yourself. I’d emphasize that PowerCenter Express doesn’t replace the need for Informatica’s enterprise grade products, but it is ideal for rapid prototyping, profiling data, and developing quick proof of concepts.
PowerCenter Express provides a glimpse of the evolving Informatica platform by integrating four Informatica products into a single, compact tool. There are no database dependencies and the product installs in just under 10 minutes. Much to my own surprise, I use PowerCenter express quite often going about the various aspects of my job with Informatica. I have it installed on my laptop so it travels with me wherever I go. It starts up quickly so it’s ideal for getting a little work done on an airplane.
For example, recently I wanted to explore building some rules for an upcoming proof of concept on a plane ride home so I could claw back some personal time for my weekend. I used PowerCenter Express to profile some data and create a mapping. And this mapping wasn’t something I needed to throw away and recreate in an enterprise version after my flight landed. Vibe, Informatica’s build once / run anywhere metadata driven architecture allows me to export a mapping I create in PowerCenter Express to one of the enterprise versions of Informatica’s products such as PowerCenter, DataQuality or Informatica Cloud.
As I alluded to earlier in this article, being a free offering I honestly didn’t expect too much from PowerCenter Express when I first started exploring it. However, due to my own positive experiences, I now like to think of PowerCenter Express as the Swiss Army Knife of Data Integration.
To start claiming back some of your personal time, get started with the free version of PowerCenter Express, found on the Informatica Marketplace at: https://community.informatica.com/solutions/pcexpress
After I graduated from business school, I started reading Fortune Magazine. I guess that I became a regular reader because each issue largely consists of a set of mini-business cases. And over the years, I have even started to read the witty remarks from the managing editor, Andy Serwer. However, this issue’s comments were even more evocative than usual.
Connectivity is perhaps the biggest opportunity of our time
Andy wrote, “Connectivity is perhaps the biggest opportunity of our time. As technology makes the world smaller, it is clear that the countries and companies that connect the best—either in terms of, say traditional infrastructure or through digital networks are in the drivers’ seat”. Andy sees differentiated connectivity as involving two elements–access and content. This is important to note because Andy believes the biggest winners going forward are going to be the best connectors to each.
Enterprises need to evaluate how the collect, refine, and make useful data
But how do enterprises establish world class connectivity to content? I would argue–whether you are talking about large or small data—it comes from improving an enterprise’s abiity collect, refine, and create useful data. In recent CFO research, the importance of enterprise data gathering capabilities was stressed. CFOs said that their enterprises need to “get data right” at the same time as they confirmed that their enterprises in fact have a data issue. The CFOs said that they are worried about the integrity of data from the source forward. And once they manually create clean data, they worry about making this data useful to their enterprises. Why does this data matter so much to the CFO? Because as CFOs get more strategic, they are trying to make sure their firms drive synergies across their businesses.
Business need to make sense of data and get it to business users faster
One CFO said it this way, “data is potentially the only competitive advantage left”. Yet another said, “our businesses needs to make better decisions from data. We need to make sense of data faster.” At the same time leading edge thinkers like Geoffrey Moore has been suggesting that businesses need to move from “systems of record” applications to “system of engagement” applications. This notion suggests the importance of providing more digestible apps, but also the importance of recognizing that the most important apps for business users will provide relevant information for decision making. Put another way, data is clearly becoming fuel to the enterprise decision making.
“Data Fueled Apps” will provide a connectivity advantage
For this reason, “data fueled” apps will be increasingly important to the business. Decision makers these days want to practice “management by walking around” to quote Tom Peter’s Book, “In Search of Excellence”. And this means having critical, fresh data at their fingertips for each and every meeting. And clearly, organizations that provide this type of data connectivity will establish the connectivity advantage that Serwer suggested in his editor comments. This of course applies to consumer facing apps as well. Server, also, comments on the impacts of Apple and Facebook. Most consumers today are far better informed before they make a purchase. The customer facing apps, for example Amazon, that have led the way have provided the relevant information for the consumer to inform them on their purchase journey.
Delivering “Data Fueled Apps” to the Enterprise
But how do you create the enterprise wide connectivity to power the “Data Fueled Apps?” It is clear from the CFOs comments work is needed here. That work involves creating data which is systematically clean, safe, and connected. Why does this data need to be clean? The CFOs we talked to said that when the data is not clean then they have to manually massage the data and then move from system to system. This is not providing the kind of system of engagement envisioned by Geoffrey Moore. What this CFO wants to move to a world where he can access the numbers easily, timely, and accurately”.
Data, also, needs to be safe. This means that only people with access should be able to see data whether we are talking about transactional or analytical data. This may sound obvious, but very few isolate and secure data as it moves from system to system. And lastly, data needs to be connected. Yet another CFO said, “the integration of the right systems to provide the right information needs to be done so we have the right information to manage and make decisions at the right time”. He continued by saying “we really care about technology integration and getting it less manual. It means that we can inspect the books half way through the cycle. And getting less manual means we can close the books even faster. However, if systems don’t talk (connect) to one another, it is a big issue”.
Finally, whether we are discussing big data or small data, we need to make sure the data collected is more relevant and easier to consume. What is needed here is a data intelligence layer provides easy ways to locate useful data and recommend or guide ways to improve the data. This way analysts and leaders can spend less time on searching or preparing data and more time on analyzing the data to connect the business dots. This can involve mapping data relationship across all applications and being able to draw inferences from data to drive real time responses.
So in this new connected world, we need to first set up a data infrastructure to continuously make data clean, safe, and connected regardless of use case. It might not be needed to collect data, but the data infrastructure may be needed to define the connectivity (in the shape of access and content). We also need to make sure that the infrastructure for doing this is reusable so that the time from concept to new data fueled app is minimized. And then to drive informational meaning, we need to layer on top the intelligence. With this, we can deliver “data fueled apps” that enable business users the access and content to drive better business differentiation and decisioning!
I have a little fable to tell you…
This fable has nothing to do with Big Data, but instead deals with an Overabundance of Food and how to better digest it to make it useful.
And it all started when this SEO copywriter from IT Corporation walked into a bar, pub, grill, restaurant, liquor establishment, and noticed 2 large crowded tables. After what seemed like an endless loop, an SQL programmer sauntered in and contemplated the table problem. “Mind if I join you?”, he said? Since the tables were partially occupied and there were no virtual tables available, the host looked on the patio of the restaurant at 2 open tables. “Shall I do an outside join instead?” asked the programmer? The host considered their schema and assigned 2 seats to the space.
The writer told the programmer to look at the menu, bill of fare, blackboard – there were so many choices but not enough real nutrition. “Hmmm, I’m hungry for the right combination of food, grub, chow, to help me train for a triathlon” he said. With that contextual information, they thought about foregoing the menu items and instead getting in the all-you-can-eat buffer line. But there was too much food available and despite its appealing looks in its neat rows and columns, it seemed to be mostly empty calories. They both realized they had no idea what important elements were in the food, but came to the conclusion that this restaurant had a “Big Food” problem.
They scoped it out for a moment and then the writer did an about face, reversal, change in direction and the SQL programmer did a commit and quick pivot toward the buffer line where they did a batch insert of all of the food, even the BLOBS of spaghetti, mash potatoes and jello. There was far too much and it was far too rich for their tastes and needs, but they binged and consumed it all. You should have seen all the empty dishes at the end – they even caused a stack overflow. Because it was a batch binge, their digestive tracts didn’t know how to process all of the food, so they got a stomach ache from “big food” ingestion – and it nearly caused a core dump – in which case the restaurant host would have assigned his most dedicated servers to perform a thorough cleansing and scrubbing. There was no way to do a rollback at this point.
It was clear they needed relief. The programmer did an ad hoc query to JSON, their Server who they thought was Active, for a response about why they were having such “big food” indigestion, and did they have packets of relief available. No response. Then they asked again. There was still no response. So the programmer said to the writer, “Gee, the Quality Of Service here is terrible!”
Just then, the programmer remembered a remedy he had heard about previously and so he spoke up. “Oh, it’s very easy just <SELECT>Vibe.Data.Stream from INFORMATICA where REAL-TIME is NOT NULL.”
Informatica’s Vibe Data Stream enables streaming food collection for real-time Big food analytics, operational intelligence, and traditional enterprise food warehousing from a variety of distributed food sources at high scale and low latency. It enables the right food ingested at the right time when nutrition is needed without any need for binge or batch ingestion.
And so they all lived happily ever after and all was good in the IT Corporation once again.
Download Now and take your first steps to rapidly developing applications that sense and respond to streaming food (or data) in real-time.
The conversation at the Gartner Enterprise Architecture Summit was very interesting last week. They central them for years had been idea of closely linking enterprise architecture with the goals and strategy. This year, Gartner added another layer to that conversation. They are now actively promoting the idea of enterprise architects as strategists.
The reason why is simple. The next wave of change is coming and it will significantly disrupt everybody. Even worse, your new competitors may be coming from other industries.
Enterprise architects are in a position to take a leading role within the strategy process. This is because they are the people who best understand both business strategy and technology trends.
Some of the key ideas discussed included:
- The boundaries between physical and digital products will blur
- Every organization will need a technology strategy to survive
- Gartner predicts that by 2017: 60% of the Global 1,000 will execute on at least one revolutionary and currently unimaginable business transformation effort.
- The change is being driven by trends such as mobile, social, the connectedness of everything, cloud/hybrid, software-defined everything, smart machines, and 3D printing.
I agree with all of this. My view is that this means that it is time for enterprise architects to think very differently about architecture. Enterprise applications will come and go. They are rapidly being commoditized in any case. They need to think like strategists; in terms of market differentiation. And nothing will differentiate an organization more than their data. Example: Google autonomous cars. Google is jumping across industry boundaries to compete in a new market with data as their primary differentiator. There will be many others.
Years of thinking of architecture from an application-first or business process-first perspective have left us with silos of data and the classic ‘spaghetti diagram” of data architecture. This is slowing down business initiative delivery precisely at the time organizations need to accelerate and make data their strategic weapon. It is time to think data-first when it comes to enterprise architecture.
You will be seeing more from Informatica on this subject over the coming weeks and months.
Take a minute to comment on this article. Your thoughts on how we should go about changing to a data-first perspective, both pro and con are welcomed.
Also, remember that Informatica is running a contest to design the data architecture of the year 2020. Full details are here.