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Titlesoftware memories -- history of the software industry, its companies and its personalities

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Description history of the software industry by curt monash, who\'s been in the middle of it since 1981

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Keywords enterprise software, software industry, history
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abstract datatypes and extensible rdbms
ai memories — expert systems
historical notes on artificial intelligence
notes on the technology supporting packaged application software
enterprise application software — vertical and departmental markets
enterprise application software — generalities
application databases
corporate culture in enterprise it — the dignity crowd
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enterprise application.
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the history of expert systems http://www.softwarememories.com/2015/12/03/ai-memories-expert-systems/
a general present-day overview of the artificial intelligence business http://www.dbms2.com/2015/12/01/what-is-ai-and-who-has-it/
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--> home about contact feeds december 12, 2015 abstract datatypes and extensible rdbms in my recent stonebraker-oriented post about database theory and practice over the decades, i wrote i used to overrate the importance of abstract datatypes, in large part due to mike’s influence. i got over it. he should too. they’re useful, to the point of being a checklist item, but not a game-changer. a big part of the problem is [that] different parts of a versatile dbms would prefer to do different things with memory. and then left an iou for a survey of abstract datatypes/rdbms extensibility. let’s get to it. perhaps the most popular term was actually object/relational dbms, but i’ve never understood the etymolygy on that one. although i call rdbms extensibility a “checklist item”, the list of products that can check it off is actually pretty short. postgresql has the granddaddy implementation. its ideas were commercialized as illustra, which was bought by informix, which later was bought by ibm. oracle has one of the major implementations. ibm has one of the major implementations. sybase has struggled with implementing the technology. so did microsoft sql server, which of course started with the sybase code line. surely there are more, but at the moment i can’t really think of which they are. read more categories: database management systems, ibm, informix, ingres, microsoft, oracle, sybase 1 comment --> december 3, 2015 ai memories — expert systems this is part of a four post series spanning two blogs. one post gives a general historical overview of the artificial intelligence business. one post (this one) specifically covers the history of expert systems. one post gives a general present-day overview of the artificial intelligence business. one post explores the close connection between machine learning and (the rest of) ai. as i mentioned in my quick ai history overview, i was pretty involved with ai vendors in the 1980s. here on some notes on what was going on then, specifically in what seemed to be the hottest area at the time — expert systems. summing up: the expert systems business never grew to be very large, but it garnered undue attention (including from me). in particular, the companies offering the technology didn’t prosper much. what commercial investment there was in expert system projects, successful or otherwise, foreshadowed some of what would be tried using other analytic technologies. application areas included, among others, credit granting, financial trading, airline flight pricing and equipment maintenance. technological reasons the industry failed included: the difficulties of debugging and maintaining a collection of rules. lack of ability to crunch data, or to benefit from data crunching. (this is surely why few expert systems use cases were in the marketing area.) a paradigm that assumed the required rules pre-existed inside expert humans’ heads. there were some successful projects even so. first, some basics.  read more categories: artificial intelligence, fun stuff 4 comments --> december 1, 2015 historical notes on artificial intelligence this is part of a three post series spanning two blogs. one post (this one) gives a general historical overview of the artificial intelligence business. one post specifically covers the history of expert systems. one post gives a general present-day overview of the artificial intelligence business. one post explores the close connection between machine learning and (the rest of) ai. 0. the concept of artificial intelligence has been around almost as long as computers — or even before, if you recall that robots were imagined by the 1920s. but for a while it was mainly academic and perhaps military/natural security research. there’s been a robotics industry for over 50 years. but otherwise, when i first became an analyst in 1981, ai commercialization efforts were rather new, and were concentrated in three main areas: expert systems. natural language query. general ai underpinnings (especially lisp machines). 1. if i’ve ever gotten too close to a group of companies, it was probably the 1980s ai vendors. i unfortunately earned investment banking fees by encouraging people into money-losing investments in all three areas cited above, in teknowledge, artificial intelligence corporation and symbolics respectively. i dated women who worked for symbolics and teknowledge. i wrote and performed a satirical song about inference at an employee party for intellicorp. accordingly, when i write about individual companies in the sector, i fear that i may go on at self-indulgent length. so i’ll save all that for another time, and content myself now with a brief and dry survey that does little more than establish some context. 2. the 1980s also saw military-funded research into autonomous vehicles, as well as continued efforts in robotics and machine vision. frankly, there wasn’t a lot of commercial overlap between these areas and the rest of ai at that time, and the rest of ai is what i tracked more closely. but in one counterexample, a machine vision company named machine intelligence spun off a company that was building a pc dbms with some natural language query capability. the spin-off company was symantec. (obviously, symantec his pivoted multiple times since.) machine intelligence cofounder earl sacerdoti also wound up at expert system vendor teknowledge for a while. so maybe there was more overlap in theory than there was in commercial practice.  read more categories: artificial intelligence 4 comments --> november 11, 2015 notes on the technology supporting packaged application software this is part of a three-post series on enterprise application software over the decades, meant to serve as background to a dbms2 post on issues in enterprise apps. the first lays out very general issues in understanding and subdividing this multi-faceted sector. the second calls out characteristics of specific application areas. the third (this one) discusses application software products’ underlying technology. 0. i’d like to discuss the technology underneath packaged application software. to create some hope of the discussion being coherent, let’s split apps into a few categories: major/core suite, large enterprises – e.g. erp (enterprise resource planning). major/core suite, smaller enterprises — e.g., the province of progress and intersystems vars (value-added resellers). remarkably distributed applications. this is where a lot of the more unusual technology choices cluster. other point solutions. sometimes, a guy just needs a catch-all category. 1. the idea of bundling erp (or its predecessor mrp) with an underlying dbms has been around for a long time. cullinet and cincom tried it, but with pre-relational dbms. oops. oracle has always had that strategy. a sizable minority of sap’s customers ran and for smaller enterprises, it has been the norm, not the exception. read more categories: application software, cullinet, database management systems, ibm, informix, microsoft, oracle, pre-relational era, sap, sybase 3 comments --> november 11, 2015 enterprise application software — vertical and departmental markets this is part of a three-post series on enterprise application software over the decades, meant to serve as background to a dbms2 post on issues in enterprise apps. the first lays out very general issues in understanding and subdividing this multi-faceted sector. the second (this one) calls out characteristics of specific application areas. the third discusses application software products’ underlying technology. 1. when i started as an analyst in 1981, manufacturers seemed to still be over 40% of the it market. for them, the distinction between “cross-industry” and “vertical market” application software wasn’t necessarily clear. indeed, erp (enterprise resource planning) can be said to have grown out of the combination of mrp and accounting software, although it never was a manufacturing-specific industry category. erp also quickly co-opted what was briefly its own separate category, namely scm (supply chain management) software. 2. manufacturing aside, other important early vertical markets were banking, insurance and health care. it is no coincidence that these are highly regulated industries; regulations often gave a lot of clarity as to how software should or shouldn’t work. indeed, the original application software package category was probably general ledger, and the original general ledger packages were probably for banks rather than cross-industry. read more categories: application software, pre-relational era 4 comments --> november 11, 2015 enterprise application software — generalities this is part of a three-post series on enterprise application software over the decades, meant to serve as background to a dbms2 post on issues in enterprise apps. the first (this one) lays out very general issues in understanding and subdividing this multi-faceted sector. the second calls out characteristics of specific application areas. the third discusses application software products’ underlying technology. 1. there can actually be significant disagreement as to what is or isn’t an enterprise application. i tend to favor definitions that restrict the category to (usually) server software, which manages transactions, customer interactions, financial records and things like that. some other definitions are even more expansive, including personal productivity software such as microsoft office, computer-aided engineering systems and the like. 2.  historically, application software has existed mainly to record and route information, commonly from people to machines and back. indeed, one could say that applications are characterized by (up to) five (overlapping) aspects, which may be abbreviated as: database design. workflow/business process. user interface. social/collaboration. analytics. the first four of those five items fit into my “record and route information” framework. read more categories: application software, microsoft, oracle, sap 5 comments --> august 7, 2015 application databases in my recent post on data messes, i left an iou for a discussion of application databases. i’ve addressed parts of that subject before, including in a 2013 post on data model churn and a 2012 post on enterprise application history, both of which cite examples mentioned below. still, there’s a lot more that could be said, because the essence of an operational application is commonly its database design. so let’s revisit some history. in many cases, installing an application allows enterprises to collect the underlying data, electronically, for the first time ever. in other cases the app organizes data that was already there in some previous form. either way, applications tend to greatly change the way data is managed and stored. read more categories: application software, sap 4 comments --> march 30, 2015 corporate culture in enterprise it — the dignity crowd these days, when one thinks of corporate culture in the tech industry, what comes to mind are probably: internet juggernauts — google, facebook and their younger siblings. the cheapskates at amazon. brogrammers. etc. most of that is at the internet companies, although there are exceptions — any kind of companies can have ping-pong tables, beanbag chairs, and a bunch of dogs* running around the office. *i mean literal pooches, not bad products. wibidata used to even post headshots of the dogs on their employee page. but there was a time, before the internet era, when similar things could be said of enterprise it companies. the biggest fuss about culture was perhaps made among the more buttoned-down crowd, including ibm (most famously), msa (the example that made me think of this subject), and eds (who commissioned a ken follett book about themselves). they are all i have space for in this post. but there were also the beginnings of recognizable silicon valley start-up culture, and i hope to discuss that in the future. the dignity crowd i still chuckle when i see an ibmer in a company-issued polo shirt, because there was a time when ibm had a strict dress code of conservative suits and ties. along with that went never drinking alcohol in a customer setting, in an era when boozy business meals were the norm. the point of all these rules, i think, was twofold. first, ibm wanted to be seen as a trusted, dignified adviser to customer organizations. second, ibm generally wanted some kind of rules so that the behemoth corporation would be a team. and ibm was more than a collection of people; it was an organization. employees with 20+ year service might average one city-to-city move per year. (hence the joke that ibm stood for i’ve been moved.) but whoever was involved with your account — if your systems stopped working, ibm would do whatever it took to get you back running fast. and a large fraction of ibm’s sales effort was spreading fud (fear, uncertainty and doubt) as to whether rival vendors would care for customers equally well. eds (electronic data systems, founded by ross perot) fancied itself as a cross between ibm and the us military. even computer operators had to be clean-shaven and wear jacket and tie. a large fraction of hires were military veterans,* and an extreme “do it now! no excuses for failure will be accepted!” ethos flowed through the company.  read more categories: eds, ibm, msa 3 comments --> march 30, 2015 john imlay, the jolliest huckster john imlay passed away last week. let me start by saying: john was a jolly huckster. of the entrepreneurs i’ve known with manic amounts of sales energy, he’s the one i can least imagine saying or doing an unkind thing. indeed, the breathless bit about john’s “kindheartedness” toward the end of this 2010 article doesn’t ring too false.* john wasn’t technically the founder of msa, but he might as well have been. (analogy: steve case at aol.) when he got there, it was management science atlanta, a failing hodgepodge of tiny businesses. he turned into management science america, a leading software company of its day, and the one that “should” have become what sap is today. my 2006 post on msa memories has 90 comments, the vast majority of which are from former msa employees who loved working there. *not as persuasive is the story about the missed chance to buy microsoft in 1981. i knew a lot of folks at msa in the 1980s, and nobody ever mentioned that. also, the story has an obviously wrong microsoft fat (what city it was in). john imlay was a showman, best known for giving speeches with live animals or other dramatic visual aids, as per this short 1994 new york times interview. but he was also a tireless, lead-from-the-front seller. an msa salesman who booked john into an exhausting schedule of sales calls could expect a return visit from his ceo soon, because he was using imlay’s time optimally. indeed, i didn’t really know john all that well, probably for a couple of reasons: he was rarely around when i visited; he was much more likely to be out on the road selling. this was back in my stock analyst days, and i generally spent more time with detail-oriented folks, numbers- and product-oriented ones alike. read more categories: cullinet, msa 2 comments --> september 22, 2014 larry ellison memories larry ellison had an official job change, and will be cto and executive chairman of oracle — with the major product groups reporting to him — instead of ceo. i first met larry 31 years ago, and hung out with him quite a bit at times. so this feels like time for a retrospective. for starters, let me say: i met larry ellison the same year i learned of him, which was 1983. we were in fairly active touch until the late 1990s. then we drifted apart. that period corresponds roughly to the eras i characterized in my oracle history overview as hypergrowth, plateau, and professionalism. with larry as with other “larger than life” industry figures i’ve met, what you get in private and what you see in public are pretty similar. i’ve had high-intensity dinner conversations with larry (numerous times), bill gates (a few times) and ross perot (once) that are quite in line with their public demeanors. with larry, facts can be mutable things. the first time i met him, i came away with the impression he had a phd. the second time, it was only a masters degree. ten years later, he’d almost graduated from the university of chicago, but had failed or not take a french exam. and i gather his educational resume has retreated a little further since. larry is hilarious, in a scathing way, and an excellent story-teller. unfortunately, his humor rarely translates well to out-of-context print. some anecdotes: read more categories: database management systems, oracle 2 comments --> next page → subscribe to the monash research feed via rss or email: login search our blogs and white papers --> monash research blogs dbms 2 covers database management, analytics, and related technologies. text technologies covers text mining, search, and social software. strategic messaging analyzes marketing and messaging strategy. the monash report examines technology and public policy issues. software memories recounts the history of the software industry. user consulting building a short list? 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