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Data

data-silos-architecture

Data is an essential part of every PLM implementation. It all starts from data – design, engineering, manufacturing, supply chain, support, etc. Enterprise systems are fragmented and representing individual silos of enterprise organization. To manage product data located in multiple enterprise data silos is a challenge for every PLM implementation.

To “demolish enterprise data silos” is a popular topic in PLM strategies and deployments. The idea of having one single point of truth is always in mind of PLM developers. Some of my latest notes about that here – PLM One Big Silo.

MCADCafe article – Developing Better Products is a “Piece of Cake” by Scott Reedy also speaks about how PLM implementation can help to aggregate all product development information scattered in multiple places into single PLM system. The  picture from the article presents the problem:

product-data-silos

The following passage is the most important, in my view:

Without a PLM system, companies often end up with disconnected silos of information. These silos inhibit the ability to control the entire product record and employees waste unnecessary time searching for the correct revision of the product design. As companies outsource design or manufacturing, it becomes even harder to ensure the right configuration of the product is leveraged by external partners.

Whether your company makes medical devices, industrial equipment, laptops, cell phones or other consumer products – PLM provides a secure, centralized database to manage the entire product record into a “Single Record of the Truth”… With a centralized product record, it is easy to propose and submit changes to the product design, track quality issues and collaborate with your internal teams and supply-chain partners.

The strategy of “single record of truth” is a centerpiece of each PLM implementation. However, here is the thing… if you look on the picture above you can certainly see some key enterprise  systems – ERP, CRM, MES, Project and program management, etc. PLM system can contain scattered data about product design, CAD files,  Part data, ECO records, Bill of Materials. However, some of the data will still remain in other systems. Some of the data gets duplicated. This is what happens in real world.

It made me think about 3 important data architecture aspects of every PLM implementation: data management, data reporting and data consistency.

Data management layer is focusing on what system is controlling data and providing master source of information.  Data cannot be mastered in multiple places. Implementation needs to organize logical split of information as well as ability to control “data truth”. This is the most fundamental part of data architecture.

Data reporting is focusing how PLM can get data extracted from multiple sources and presented in seamless way to end user. Imagine, you need to provide an “open ECO” report. The information can reside in PLM, ERP and maybe some other sources. To get right data in a right moment of time, can be another problem to resolve.

Last, but not least - data consistency. When data located in multiple places system will rely on so-called “eventual consistency” of information. The system of events and related transactions is keeping data in sync. This is not a trivial process, but many systems are operating in such way. What is important is to have a coordinated data flow between systems supporting eventual consistency and data management and reporting tools.

What is my conclusion? To demolish silos and manage single point of truth is a very good and important strategic message. However, when it comes to nuts and bolts of implementation, an appropriate data architecture must be in place to insure you will have right data at right time. Many PLM implementations are underestimating the complexity of data architecture. It leaves them with marketing slogans, burned budgets and wrong data. Just my thoughts…

Best, Oleg

picture credit MCADCafe article

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plm-no-sql-guide

People keep asking me questions about NoSQL. The buzzword “NoSQL” isn’t new. However, I found it still confusing, especially for developers mostly focusing on enterprise and business applications. For the last decade, database technology went from single decision to much higher level of diversity. Back in 1990s, the decision of PDM/PLM developers was more or less like following – “If something looks like document, use Excel and Office. Otherwise, use RDBMS”. Not anymore. My quick summary of NoSQL was here – What PLM vendors need to know about NoSQL databases. You can go more deep in my presentation – PLM and Data Management in 21st century. If you feel more “geeky”, and considering  maybe summer development projects, I can recommend you the following book – 7 Database in 7 weeks.

John De Goes blog post The Rise (and Fall?) of NoSQL made me think how to explain the need of NoSQL for PLM implementers, architects and developers. In a nutshell, here is the way I’d explain that – NoSQL databases allow you to save variety of specific data in a much simple way, compared to SQL structured information. So, use right tool for the right job – key/value; document; graph, etc.

So, NoSQL is accelerating development of cloud and mobile apps. It became much faster since some specific NoSQL databases tuned for particular type of non-structured data:

With NoSQL: (1) Developers can stuff any kind of data into their database, not just flat, uniform, tabular data. When building apps, most developers actually use objects, which have nesting and allow non-uniform structure, and which can be stored natively in NoSQL databases. NoSQL databases fit the data model that developers already use to build applications. (2) Developers don’t have to spend months building a rigid data model that has to be carefully thought through, revised at massive cost, and deployed and maintained by a separate database team within ops.

However, everything comes with price. The important insight of the article is to point on how data can be reused for reporting and other purposes. The following passage summarizes the most visible part of what is missing in NoSQL:

It’s quite simple: analytics tooling for NoSQL databases is almost non-existent. Apps stuff a lot of data into these databases, but legacy analytics tooling based on relational technology can’t make any sense of it (because it’s not uniform, tabular data). So what usually happens is that companies extract, transform, normalize, and flatten their NoSQL data into an RDBMS, where they can slice and dice data and build reports.

PDM and PLM products are evolving these days from early stage of handling “records of metadata” about files towards something much more complicated – large amount of data, unstructured information, video, media, processes, mobile platforms, analytics. CAD/PLM vendors are pushing towards even more complicated cloud deployment. The last one is even more interesting. The need to rely on customer RDBMS and IT alignment is getting lest restrictive. So, the opportunity to choose right database technology (aka the right tool for a job) is getting more interesting.

What is my conclusion? Database technologies universe is much more complicated compared to what we had 10-15 years ago. You need to dig inside into data management needs, choose right technology or tool to be efficient. One size doesn’t fit all. If you want to develop an efficient application, you will find yourself using multiple data management technologies to handle data efficiently. Just my thoughts…

Best, Oleg

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PLM One Big Silo

by Oleg on June 9, 2014 · 3 comments

plm-one-big-silo

Silos is an interesting topic in enterprise software. And it is a very important topic for product lifecycle management. Why so? Because, PLM is heavily relies on the ability to work and communicated across the organization and extended value chain. Accessing information in multiple departments, functional domains and application is part of this story. Silos is clearly one of the biggest PLM challenges. At the same time, silos can be also a good thing. They are reflection of org structure and sort of order we can use to navigate inside of organization.

Engineering.com posted PLM/ERP article – “Demolish the silos in PLM”: Why Dassault’s Bernard Charles believes in the 3D Experience. Read the article and draw your opinion. My understanding – Dassault System is combine multiple technologies and product belonging to different organizational domains to improve communication and information access across silos in organization.

Dassault System is not alone in the try to crush silos. Article is referencing other PLM companies’ effort to interconnect people and products. I liked the following passage:

The main idea behind DS’ 3DExperience is to provide the IT tools needed to break down the silos and connect the development work not only to software, electronics and manufacturing, but also to the end-customers.  No doubt there are similarities and touch points between what this solution aims to do and Siemens PLM’s Industry 4.0 concept as well as PTC’s broader ALM, MES and SLM/IoT scope. The difference is that Siemens PLM places a higher priority on the engineering side of product realization, whereas PTC presently zooms in on the aftermarket and product-as-a-service concept. 

Interesting enough, web is also got infected with the problem of silos. Large web 2.0 platforms are very similar to enterprise software silos, which put a lot of questions about availability of information across the web. There are quite lot of debates these days around the topic of web openness and information access. I’ve been reading Aral Balkan’s article – How Web 2.0 killed the Internet. The article contains a lot of controversial opinions about development of Web 2.0 and the way Open API used to support the development of huge centralized systems such as Facebook, Google, LinkedIn, Twitter and some others.

The thing that made me think the most was the question about Openness and Open APIs. Here is the passage from the article.

An Open API is simply a limited, revokable license to access and consume a certain subset of data and/or functionality that belongs to a closed silo. It is a visitor’s pass. The terms of the pass grant you limited access for a specific time. The terms can be altered — and routinely are altered — at the whim of the API owner. This is a painful lesson that many developers learned, for example, while working to add value to the Twitter platform by building Twitter clients. They were unceremoniously dumped after expending their energies to help Twitter build up its closed silo.

These two articles made me think about demolishing organizational silos, enterprise software, and future trajectories of PLM development. The term silos is misleading. There are organizational silos and application silos. The first (organizational silos) is something that needs to be demolished to improve communication and process transparency. However, the second one (applications) is something that will be built-up to connect people, applications and data. So, there is a high probability to have PLM One Big Silo built to solve the problem of communication and streamlining of product development.

The thing that raises my concern are related to open API. Enterprise software companies might have different reasons to product data compared to Google, Facebook and Twitter. However, fundamentally these APIs are controllable by vendors that can turn them off and on depends on the strategy, competition and many other reasons.

What is my conclusion? To build an open system is a very complicated task. I can see a shift towards creating of huge monolithic vertical silos. So, PLM One Big Silo is a very possible future for customers looking for smoothly integrated systems and aligned experience. However, my belief is that future will belong to open systems, which will bring an additional level of innovation and flexibility. Long term commitment of vendors for Open API is an important indication of software trajectory. Just my thoughts…

Best, Oleg

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Will PLM Vendors Jump into Microsoft Cloud Window in Europe?

April 10, 2014

Cloud is raising lots of controversy in Europe. While manufacturing companies in U.S. are generally more open towards new tech, European rivals are much more conservative. Many of my industry colleagues in Germany, France, Switzerland and other EU countries probably can confirm that. Europe is coming to cloud systems, but much slower. I’ve been posting […]

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How cloud PLM can reuse on-premise enterprise data?

April 7, 2014

Cloud becomes more and more an obsolete additional word to call every technology we develop I hardly can image anything these days that we develop without “cloud in mind”. This is absolutely true about PLM. Nowadays, it is all about how to make cloud technologies to work for you and not against you. For cloud […]

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Why PLM vendors need to hire data scientists?

December 4, 2013

The importance of data is growing tremendously. Web, social networks and mobile started this trend just few years ago. However, these days companies are starting to see that without deep understanding of data about their activities, the future of company business is uncertain. For manufacturing companies, it speaks a lot of about fundamental business processes […]

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Why PLM can be infected by digital schizophrenia?

November 13, 2013

Our life is getting more complex everyday. The time when we’ve been localized by our personal computer and document files gone forever. The complexity came from connectivity – networks and emails. For the last decade it was exposed even more with the web and mobile. We are overloaded with the information coming from different places […]

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How CAD/PLM can capture design and engineering intent

November 8, 2013

It was a big Twitter day. Twitter IPO generated an overflow of news, articles, memorable stories. For me, twitter become a part of my working eco-system, the place I use to capture news, exchange information and communicate with people. If you are on twitter, try Vizify to visualize you twitter account. I did it here. […]

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Why PLM should friend Chief Data Officer?

October 23, 2013

Technology space is good about inventing new jobs, titles and responsibilities. Until now, we knew about CEO, COO, CIO… The last one was a very important guy when it came to the decision point about enterprise software. PLM included. The dream of every PLM vendor and implementer was to get closer to CIO to influence […]

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