Aggregated enterprise architecture wisdom
Discourse with Dr. Barry Robson, about some thing quite bizarre in solving an unknown problem against uncertainty. Srinidhi Boray (SB) – Hey Barry Question !!! “Graphing should pave way for creating the tacit knowledge by context for a chosen hypothesis; and infinite varieties of the hypothesis is technically possible in an ecosystem” Dr. Barry Robson (BR) – Your question […]
It’s never been as important to reach outside of the business as it is in the digital world of today. From an architects perspective it is vital to be able to connect the dots between what is servicing and who is being served. This little card is designed to help you go fast by staying small and […]
I said that 2015 would be a tough year for enterprise data and analytics vendors in my spring report, “Brief: Turning Big Data Into Business Insights, 2015.” I thought two things would happen. First, open source would drag on vendors’ revenues as demand for big expensive products declined. Second, the cloud would create revenue headaches. Turns out, I was right. Teradata’s midyear earnings were down 8%, and IBM reported that Q2 revenue was down 12% from a year ago. As further proof, consider the rash of data management vendors running for private equity (e.g. Dell/EMC, Informatica, and TIBCO). It’s been tough times indeed, even though most vendors are keeping their messaging positive to reassure buyers and investors.
Over the past two weeks, I attended Teradata Partners in Anaheim and IBM Insight in Las Vegas — giving me a firsthand look at how two giants of the data and analytics industry are handling disruption. What I saw was a tale of two vendors that couldn’t be any more different:
I said that 2015 would be a tough year for enterprise data and analytics vendors in my spring report, “Brief: Turning Big Data Into Business Insights, 2015.” I thought two things would happen. First, open source would drag on vendors’ revenues as demand for big expensive products declined. Second, the cloud would create revenue headaches. Turns out, I was right. Teradata’s midyear earnings were down 8%, and IBM reported that Q2 revenue was down 12% from a year ago. As further proof, consider the rash of data management vendors running for private equity (e.g. Dell/EMC, Informatica, and TIBCO). It’s been tough times indeed, even though most vendors are keeping their messaging positive to reassure buyers and investors.
Over the past two weeks, I attended Teradata Partners in Anaheim and IBM Insight in Las Vegas — giving me a firsthand look at how two giants of the data and analytics industry are handling disruption. What I saw was a tale of two vendors that couldn’t be any more different:
It is probably true to say that every book has one major theme running through it, and probably a few sub-themes. Writing the second edition of a book is a great opportunity to revisit its primary topic to see whether it is still relevant or not. I found it really interesting to revisit the book I wrote with Elaine over ten…
I’m looking forward to speaking about trends in enterprise architecture at the EA2015 conference this week on 4 November in Copenhagen. Having spoken at this annual conference over the past several years, it has become my annual “state-of-the-union” address to the Danish EA community. This year, I will talk about several trends and issues. The outline of the lecture looks […]
Now that I’m in the wrap-up phase for my Australian EA tour, how did it go? Pretty good, would be the short answer. A bit disappointing in certain aspects, but otherwise much what I’d hoped to see: real signs of progress…
Sharing a method to help resolve this challenge and help focus on what is important so you can expend your nervous system solving problems rather than creating them. Armed with a true understanding of the organizational dynamics it is now a good time to revisit a first principal to help resolve what is an important and urgent problem.
To avoid the ever debate on the scope of Enterprise Architecture, IT vs the enterprise, I call Enterprise Modelling, rather than Enterprise Architecture (EA), the enterprise wide architecture, that covers business, technology and people.
I’m looking forward to speaking about trends in enterprise architecture at the EA2015 conference on 4 November in Copenhagen. Having spoken at this annual conference over the past several years, it is my annual “state-of-the-union” address to the Danish EA community. This year, I will talk about several trends and issues. The outline of the lecture looks like this: The […]
You can’t bring up semantics without someone inserting an apology for the geekiness of the discussion. If you’re a data person like me, geek away! But for everyone else, it’s a topic best left alone. Well, like every geek, the semantic geeks now have their day — and may just rule the data world.
It begins with a seemingly innocent set of questions:
“Is there a better way to master my data?”
“Is there a better way to understand the data I have?”
“Is there a better way to bring data and content together?”
“Is there a better way to personalize data and insight to be relevant?”
Semantics discussions today are born out of the data chaos that our traditional data management and governance capabilities are struggling under. They’re born out of the fact that even with the best big data technology and analytics being adopted, business stakeholder satisfaction with analytics has decreased by 21% from 2014 to 2015, according to Forrester’s Global Business Technographics® Data And Analytics Survey, 2015. Innovative data architects and vendors realize that semantics is the key to bringing context and meaning to our information so we can extract those much-needed business insights, at scale, and more importantly, personalized.
You can’t bring up semantics without someone inserting an apology for the geekiness of the discussion. If you’re a data person like me, geek away! But for everyone else, it’s a topic best left alone. Well, like every geek, the semantic geeks now have their day — and may just rule the data world.
It begins with a seemingly innocent set of questions:
“Is there a better way to master my data?”
“Is there a better way to understand the data I have?”
“Is there a better way to bring data and content together?”
“Is there a better way to personalize data and insight to be relevant?”
Semantics discussions today are born out of the data chaos that our traditional data management and governance capabilities are struggling under. They’re born out of the fact that even with the best big data technology and analytics being adopted, business stakeholder satisfaction with analytics has decreased by 21% from 2014 to 2015, according to Forrester’s Global Business Technographics® Data And Analytics Survey, 2015. Innovative data architects and vendors realize that semantics is the key to bringing context and meaning to our information so we can extract those much-needed business insights, at scale, and more importantly, personalized.