...when you guys focus so much on the political crap.Dreamerlong IQ, BZUN, BIDU, JD, AYXwaiting to get back into: TTD, NTNXnot believing the hype on: PSTG, PVTL
Why AYX?What hype on PSTG?....they are doing 40% revenue growth YoY.....not much hype at P/S 4.6.
Referring to the hype on the TMF boards for a hardware storage company. projecting "AI" and the theme that they are really sorta like software, when they are nowhere near being a software company yet. I think they have good short-term prospects, but this isn't one I buy planning on holding past a preset gain %. Unless they become the storage default for the cloud titans, I don't see them crushing the enterprise which is laden with IT decision-makers that have years of experience with NetApp, HPE, EMC, Hitachi, IBM, etc etc... Plus Nutanix (actually more of software) and VMware going after storage space with HCI successfully. Upstarts like Rubriks and Cohesity and Nasuni gaining bandwidth among those same decisionmakers. It is just not a great market to be in, if you are tied to hardware refreshes. Hey - did they ever break out Flashblade sales yet? ---AYX, as I have often stated, is in the business of making data actionable. Higher growth rates than others in the "data" space. Recently beat down a bit. Candidly, still pricey, but higher-growth can suppress the P/S more quickly. If they do a 20% run fairly quickly, I may just sell and wait for another reentry though. Forgot to mention NVDA. Still love the company and long-term growth, just felt they may be flat-ish for a while, so putting money elsewhere for a bit. I think the market has started to realize Trump/China tariff wars have no real impact on in-China-only stock plays, such as IQ, BIDU, JD, BZUN. Adding to that list would be HUYA (think "Twitch") and MOMO (think "Match" or "Tinder") that I am ready to dabble in.Dreamer
Hey! Don’t you be getting too far away now, ya hear?please
Dreamer:SO you went long NTNX??What took you so long?
I had been long NTNX previously, but given the sketchy responses to ERs this Q, and fact they had a great run-up, I wanted to wait until after ER.Not a huge benefit, but I am in now at same price I was in March, but I made a few bucks on the ST trade in the meantime. Barring recession or C-level implosion/scandal, I am comfortable for long-term (which is, like, a year or two for me). Will reevaluate each ER, but not planning on selling unless they go on some sick/overkill run up ala TTD.Much better LT choice than PSTG or PVTL or ANET, imo.Dreamer
OK.....I have stayed in NTNX and intend to do so until the story line changes.But let me ask you Dreamer, since you have some knowledge in this area, can you clarify these issues with AYX:Who exactly is clamoring to AYX and paying $4,000 annually. The company says they have 30 million "civil" data scientists as a TAM......who exactly are these people and why haven't they already clamored to AYX if there is such a need......especially since AYX has been a company for 20 years??It seems in my brief reading that Tableau pops up time and again for beautiful presentation of the data and repeated comments about using it with various other software......obviously the FOOL is high on DATA:http://www.stockta.com/cgi-bin/analysis.pl?symb=DATA&cob......vs this:http://www.stockta.com/cgi-bin/analysis.pl?symb=AYX&cobr......OK....it only has 23% revenue growth and half the P/S...….but it also has earnings.Can you explain the large unmet need for AYX that simpler and much less expensive solutions can't solve "adequately"......Excel and Tambleau are a mere fraction of the price.And before you say they just can't do what AYX does......what I am trying to get out is......so what......how many people need more than that and who are they???
Can you explain the large unmet need for AYX that simpler and much less expensive solutions can't solve "adequately"......Excel and Tambleau are a mere fraction of the price.And before you say they just can't do what AYX does......what I am trying to get out is......so what......how many people need more than that and who are they???---Full disclosure: I sold my AYX to buy Nutanix on the dip. :)I still love AYX, and I am not against TLND, as they are doing two different things.I am just in a high-P/S-sensitivity mode as the market volatility does not make me feel secure. So I am overweight in China stocks as a result, as they tend to be overlooked a bit and lower P/S and their growth rates are awesome right now. NTNX just fit under the bar in terms of being too pricey, but I like their story enough LT that I won't sweat it too much.Will get back in TTD on a dip or after I sell a China winner. Love them LT, but up 98% from Feb 9th...c'mon...gotta be a pullback, right?? I am sure I will regret that.NVDA - love them, but expect they trade sideways. I also thought that in about Jan 2017, so...yeah.MDB - still early, and figure I can get back in after they show the execution in another ER or two and maybe I catch them on a downward swing.---Back to AYX: I don't have specific answers for you, but I know that all companies really are trying to use their data for a competitive edge and a profit center, and for many/most, this is new. Companies use Excel and other tools, largely for finance and general trends/tracking and not in truly data-scientist-ish type of ways. But a quick search may find us some numbers:financial analysts: 300k of them in 2016 https://www.bls.gov/ooh/business-and-financial/financial-ana...Accountants: about a cool 1m https://www.statista.com/topics/2121/accounting-industry-in-...Data Analysts: 700k by 2020 per IBM/Forbes https://www.forbes.com/sites/louiscolumbus/2017/05/13/ibm-pr...I list these by job type, because most big companies have them. So rather than think about Accountant firms, think about accountants or finance folks or data analysts within large Law Firms, Brokerages, Insurance companies, Airline/trans companies, travel website companies, healthcare, SLED and FED, etc etc...As an example, HR could use the help, and every company has an HR.https://www.forbes.com/sites/bernardmarr/2018/05/04/data-dri...Currently today, Excel doesn't meet the needs for true data insights...I have seen many a nerd-produced pivot table in a powerpoint and often it is just what I refer to as "keeping score" or "delivering the news" and it isn't really actionable insights into the data.Not sure if that helps, but I see the need, but can't put a finger on the exact TAM yet.Dreamer
Not sure if that helps, but I see the need, but can't put a finger on the exact TAM yet.IMO, this needs to be ferreted out because we have seen too many examples of great technology/ability for which fewer and fewer are in need. This company has been alive for 20 years and in that time has almost $200 million in annual revenue. For a stock to hit hypergrowth, there needs to be a massive unmet need......especially when the product is 5-7 times more expensive than lesser but more beautiful Tableau.Why are so many including myself having difficulty defining this hypergrowth market for AYX and who exactly their customers are and what exact problems they solve that Excel and Tableau couldn't handle........These tech companies throw around this BS TAM number like they are believable for a venture capitalist.....but most are total WAG and many are likely total crap.So that gets us back to AYX.....why are is there some massive unmet need to and to whom is that need?
https://community.alteryx.com/88,000+ posts on the user forum...that might get you some good insight.Please join, read all the posts, and report back to us with your findings.ty,Dreamer
a lot of companies have recent explosive growth, but are not exactly brand-new.TTD founded 2009. I would say last 12 months is them "arriving" after 9 years.TWLO founded 2008...10 year old company.SHOP founded 2004...pretty much could have ignored first 12 years.and my personal favorite: NVDA founded in 1993. Successful for sure, but nobody really cared until maybe 2015, almost 22 years later.Here is Alteryx history, courtesy of wikipedia:https://en.wikipedia.org/wiki/AlteryxHistorySRC LLC, the predecessor to Alteryx, was founded in 1997 by Dean Stoecker, Olivia Duane Adams and Ned Harding. SRC developed the first online data engine for delivering demographic-based mapping and reporting shortly after being founded. In 1998, SRC released Allocate, a data engine incorporating geographically organized U.S. Census data that allows users to manipulate, analyze and map data. Solocast was developed in 1998, which was software that allowed customers to do customer segmentation analysis.In 2000, SRC LLC entered into a contract with the U.S. Census Bureau that resulted in a modified version of its Allocate software being included on CD-ROMs of Census Data sold by the Bureau.In 2006, the software product Alteryx was released, which was a unified spatial and non-spatial data environment for building analytical processes and applications.In 2010, SRC LLC changed its name to that of its core product, Alteryx.In 2011, Alteryx raised $6 million in venture funding from the Palo Alto investment arm of SAP AG, SAP Ventures. In 2013, Alteryx raised $12 million from SAP Ventures and Toba Capital. In 2014, the company raised $60 million in Round B funding from Insight Venture Partners, SAP Ventures and Toba Capital, and announced plans for a 30% workforce expansion.In 2015, Iconiq Capital led a $85 million investment in Alteryx, with Insight Venture Partners and Meritech Capital Partners also participating. Alteryx announced plans to use the new capital to expand internationally, invest in research and development, and increase its sales and marketing efforts.Alteryx announced in 2015 a new relationship with Microsoft in order to enable faster and easier data analysis through Power BI.In 2016, Alteryx was ranked #24 on the Forbes Cloud 100 list.On March 24, 2017, Alteryx went public launching their IPO at the NYSE.On February 22, 2018, Alteryx was named a leader in the 2018 Magic Quadrant for Data Science and Machine Learning Platforms. ----Just at a high-level, I think it is clear the company has always been about data, but that Alteryx as we know it started in 2010. Likely some of this has to do with the growth of cloud, as their first products were on CD-ROM, and with the founders/leaders following and capitalizing on trends with data analytics. Also, increases in computers and servers (GPUs!) and storage (tape to disc to flash) capacity started allowing for data to be used in more ways. Prior to that, companies just put "old" storage/data on tape drives in case the govt ever audited them or something.I think you are reading too much into the fact that they are a 20 year old company.If they had been selling carpet or repairing bowling ball-return machines or making elevator equipment and now they were "in the data analytics business" I would be more concerned. As it is, Gartner and the industry rates them highly.Every concern you have on AYX you could also have on TLND, although it isn't as expensive, but I believe that has more to do with the value of what each business provides (cleaning data vs actionable insights).Dreamer
Every concern you have on AYX you could also have on TLND, although it isn't as expensive, but I believe that has more to do with the value of what each business provides (cleaning data vs actionable insights).TLND has a value proposition......87 times less expensive and any company will need that/want that......AYX is more expensive solution that lesser capable DATA and Excel.The comparison is not the same.I can define for you, and have, what the investment thesis is with TLND......it is a much greater challenge to do so for AYX.As to the 20 year comment.....it was merely pointing out that we should be able to define...."why now" is the time for AYX.....what is the massive need.Can't say it any clearer than that and your inability to answer isn't a reflection on you so much as the vagueness of its investment thesis.BTW, both companies have similar growth rates......TLND is a classic innovators dilemma against Informatica.......
<<<I can define for you, and have, what the investment thesis is with TLND......it is a much greater challenge to do so for AYX.>>>No it is not. AYX brings data analysis to everyone in a package so good that it will catch on in organization like free hot cakes.What AYX is selling is utterly transformative. I mean seriously. Read a few of their case studies from customers. It takes jobs that take months to do and does them in hours or even minutes. It takes jobs that take 2+ hours per day (and sometimes weekends) and does them in 5 minutes a day.It enables business interns, just out of college, to take 30 different automotive surveys, 500 columns wide, and thousands of rows long, and with little supervision, downloading the free 14 day version of AYX's primary program, a few days to come up with insights sufficient to even please senior analysts at the company.This after giving these interns a project first, without telling them about AYX, and having them spend days and days trudging though it, with not great results, and then finding out the same project would take them 15 minutes on AYX, with far better and usable results.It goes virile within an organization. Not just analyst, but with auditors, tax accountants, it could be used by lawyers in big cases that have large databases at far less cost, and probably with better efficiency, that the very high priced, very niche pieces of software created for law firms for this purpose.Duma, this is transformative stuff.It is also not something that can just be copied and made better. I mean Excel can just be copied and made better, and has been. Who cares, you buy Excel.It enables data to be used by nearly everyone in your entire organization with self-service.If you want to stick with an Excel world that is fine. Not everyone even needs Excel, some people can get by with paper and a calculator. So what, does not change how transformative this product is.But nuff said. Each entitled to their own opinion. I know what this product is, and I know its value in the world. It is to the modern world what Excel was to the 1980s and 1990s. A far better and efficient and more agile way to do things that could not readily be done before.It only took 25 years for the next great thing to come along and replace it. Just like it only took 25 years for NoSQL to come up and start to replace Oracle SQL. Tinker
https://federalbarcle.org/product/ipad-can-litigators-best-f...Here is a CLE on how the iPad can be a litigator's best friend. Did you know, and I mean this with all sincerity and literally, that the iPad is utterly and completely disruptive to the PC, server, and everything else that came before it in litigating a case, including all the expensive and orchestrated software that exists in the world.Most lawyers simply don't believe it, so they stick with their "Excel" of litigation software. Older stuff made around 2010, which were continuation of products made earlier but improved for more mobility and larger data sets.But on the iPad using TrialPad and TranscriptPad, I can hold and organize and review and categorize and entirely litigate a case, with 25 depositions, long and detailed videos, simulations, thousands and thousands of exhibits, all with an iPad Mini, and do so with far far far less cost, and much better efficiency, without the need for technical support staff at all, and can dynamically project video and audio in the courtroom, run time spaced depositions with subtitles, review and pull out the most important parts of deposition transcripts (and in fact categorize entire depositions on the fly, far faster, far funner, with far less effort, and far better organized) than anything I can do with a staff of 5 plus technical support, plus $10k in software.Literally and adamantly, YES!!!!! Believe it or not. The software costs $129, one time fee, and only runs on iPad, and yet VERY FEW ATTORNEYS BELIEVE ME OR BELIEVE THOSE, LIKE THE MAN GIVING THIS CLE just how transformative this is.I have to say that the same is true for those who need to run large models through sizable datasets who are using complex Excel spreadsheet models, just how transformative AYX's Designer software package is, until they use it. If your work involves things simple and small enough (like mine mostly does) to use in Excel, more power to you. But if you get a more complex project, try it on the 14 day free trial for yourself.AYX is not expanding that package to handle real time streaming machine learning data for the first mile (just as Talend describes it), and expanding that package to put out such data for the enterprise in what they call the "last mile" so it can be used. TBD how quickly this catches on, if at all. It is more pricey.Disruption does not just come from being cheaper, it also comes from creating far greater power and efficiency that heretofore did not exist. Tinker
TLND is a classic innovators dilemma against Informatica…. Duma aside from the obvious age of the solutions could you go into that in more detail? Love innovator's dilemma stuff, the gift that keeps on giving, over and over.I can find info on Talend fairly easily but not so much on Informatica. If one is growing a lot faster than the other that tells you something. Since the market is a functional duopoly if Talend can beat out Informatica it will have a long runway.It's not AYX vs TLND. You can own both .I see Talent being at the narrow part of the hourglass, the waist where all that data sand is being slowed down by present solutions. That I can understand. So I am starting to overweight TLND.Less sure about AYX, I don't even use Excel in evaluating high growth tech companies. Too many assumptions ,which in fact are really guesses.
Alteryx and Talend don’t do the same thing. They are different sides of the process, which is why you don’t see them on the same graph of the Gartner Magic Quadrant. Talend is data prep. Alteryx is data analytics. Prep is pulling data in from all your sources and turning it into actionable data and all of the things that go into making that happen. Clearly there is much value in pulling your data from all of the sources that businesses collect and store data in all of the many varieties of format and getting it all into one place for a business to be able to take actions with that data. Talend produced 42% revenue growth in Q1.Analytics is taking actionable data and turning it into actionable intelligence and all of the things that go into that. It does appear that Alteryx also has solutions for no code required data prep as well, but their money maker is providing insights into what your data can tell you. Clearly there is value in gaining the intelligence of what all your data can tell you. Businesses can use that intelligence to make decisions on what products to push or change or how to run their business more efficiently, etc. AYX produced 50% revenue growth.Both present leading products in their respective fields and are easy cloud based solutions for companies to turn stores of data into (to make it short) dollars.Why will a business pay up to get these services. Because it will make them money. Far more than they pay for it.https://www.alteryx.com/productsWatch the 2 minute brief video. That’s the quickest way to see the advantage AYX brings. And you’ll know how to pronounce Alteryx.Darth
Just at a high-level, I think it is clear the company has always been about data, but that Alteryx as we know it started in 2010. Likely some of this has to do with the growth of cloud, as their first products were on CD-ROM, and with the founders/leaders following and capitalizing on trends with data analytics. Also, increases in computers and servers (GPUs!) and storage (tape to disc to flash) capacity started allowing for data to be used in more ways. Prior to that, companies just put "old" storage/data on tape drives in case the govt ever audited them or something.I think you are reading too much into the fact that they are a 20 year old company.If they had been selling carpet or repairing bowling ball-return machines or making elevator equipment and now they were "in the data analytics business" I would be more concerned. As it is, Gartner and the industry rates them highly.Pretty good synopsis of an instance of "the adjacent possible" which is key for basically any innovations/inventions.Adjacent Possible:https://www.google.com/search?q=the+adjacent+possible&rl...I think this book mentioned that phrase a pretty decent amount. It is a pretty good book.https://www.amazon.com/How-We-Got-Now-Innovations/dp/1594633...
Small tidbit from the recent Pure Storage investor presentation (which may warrant its own thread......111 slides) that factors into the Alteryx discussion is on slide 6 here.https://s21.q4cdn.com/687136699/files/doc_presentations/2018...Only 0.5% of data is analyzed as of today. This seems to be a point of carryover between the investing theses for Pure and AYX.-volfan84
TLND is a classic innovators dilemma against Informatica…. Duma aside from the obvious age of the solutions could you go into that in more detail? Love innovator's dilemma stuff, the gift that keeps on giving, over and over.Hey Mauser:It was from this thread:http://boards.fool.com/tlnd-needham-conference-33071506.aspx...Start at 16:50......where he talks about the data tax and that if Informatica type companies try to compete against TLND, they will lose their data tax.....essentially half their revenue......and even to do that, would take years to re-engineer.......this destroying their own value.Informatica will destroy itself (its value and its time) if it decides to compete against TLND for the reasons they suggest.
Tinker/Darth:I cannot make it any simpler.....you are arguing how transformative AYX technology is.....I am conceding that. I am inquiring.....who cares? Where is the massive need??Who/what desperately needs this technology because they are burning countless hours a day wasted on Excel and DATA.They claim there are 30 million "civil" data scientists as their TAM......where are they and why are they not yet clamoring for AYX?Instead of talking like a investors relations proponent.....where is the confirmation of the massive demand into the future.Please don't just throw the same transformative mumbo back.....its not about that.....its about who cares from a customer perspective......demand issue.....who really needs this degree of detail to function as business. How would AI threaten this data analytics when a person isn't required to do the mumbo.
https://www.senturus.com/blog/10-features-tableau-data-prep-...Tableau Prep has some really good, time saving features that will allow you produce Tableau friendly data. It will be a good alternative to manually scrubbing data, using steps that often are not documented or repeatable. For simple transformation logic, Tableau Prep should do everything that is required. Even though Tableau Data Prep is good at creating Tableau Data Extracts and text-based files, often it can be better to build a database repository or data warehouse that can be leveraged by multiple reporting tools. For this type of work there are other ETL (extraction, transformation and load) tools that might better suit your needs. Tools such as Alteryx and Informatica have more data output options (i.e. database tables) and more capabilities when it comes to predictive modeling, statistical analysis, geospatial manipulation, mapping and valuable built-in demographic data for enhancing a dataset. At Senturus, we believe there is no one size fits all tool for data preparation. There is a "right tool for the job" and we can help you determine what tool might best fit your needs.It is a well known fact that data preparation is often 80% of the work when building out business analytics frameworks. For more complex data work, expert advice is often needed to make sense of the underlying data sources so they can be joined into a cohesive, well-designed data model that can be used by multiple reporting tools. At Senturus, we have been doing just that for nearly two decades. We make sense of what is complex by designing and building intuitive data structures that can be easily leveraged by tools such as Tableau.
Please don't just throw the same transformative mumbo back.....its not about that.....its about who cares from a customer perspective......demand issue.....who really needs this degree of detail to function as business. How would AI threaten this data analytics when a person isn't required to do the mumbo.---I gave countless examples, with numbers of people who have job types that could benefit.You just don't like my answers, which is fine. You should just say "I disagree" rather than claim no one is providing any arguments.No one "needs" Talend.No one "needs" Google, for that matter. Or cell phones. Warren Buffett barely uses a computer or email, and he has done pretty well compared to 99.9999999% of the world's population. (just a guess on that %, btw)We don't "need" Amazon to buy products found at the mall, but a lot of us do anyway. It provided a superior service in some respects and/or we found some sort of inherent value in ordering online vs going to the mall. You could have easily said, at any time in the past 20 years, "why would anyone 'need' Amazon. Show me who needs to buy a book online when we have Borders and Barnes&Noble and other bookstores everywhere. Who needs to buy stuff from Amazon when I could just go to Sears?"For some reason you want a higher-level of certitude around the TAM of AYX than I see asked for on other investments. Perhaps it is a sense of TLND being slighted, I don't know, but I give up. I don't "need" to make you happy with my reasoning. Companies can be in business without SHOP or WIX or SQ...but they choose to use their services.I don't need air conditioning, but I choose to buy it, for a more delightful home dwelling experience.The vast majority of companies today aren't turning their massive amounts of data into actionable insights. They don't "need" to do anything about it...they could just do business as usual, but it may not help their competitive advantage in the marketplace over time.Think: Domino's pizza utilizing an online app to revitalize their biz.Think: a university that has a chat bot preprogrammed with thousands of questions providing 24/7 access for millenial-type students that expect to get their answers without talking to humans.Think: an IOT device that provides real-time updates to diet/exercise routines for diabetic patients based on their blood test results.Those are all actual examples of companies that changed their business model to stay competitive and adapt to today's "digital world".Utilizing data in an actionable way, almost regardless of the industry you are in, provided you have enough data to warrant "analysis" means you are a target for using Alteryx software to help you go above and beyond what you can get from Excel today.But you don't need to use them.Dreamer
I am talking like an investor and I see millions of seats. It not only is for those who are heavy core Excel users today with ever growing database sizes and complexity, but for those who were not, who now can be made to work with data, to spread the use of intelligent data analysis throughout the company.Here, for example is the limitations for Excel in DBA size: https://blog.dataiku.com/2016/04/26/too-big-for-excel-altern...Quite small in the scheme of things these days and will shrink even more as data grows. Then how do you share it? Keep all versions up to date? How do you make it available to persons who need data and have their own inquiries but don't have either the technical expertise and you don't want to open your spreadsheet to them?How do you resolve problems in one department and then diffuse the process throughout the organization so each department can make use of it? How do you hire data professionals, when in the end, there are only 10,000 true data professionals in the world, and you have data that needs to be analyzed in a very specific way?I gave you the example of just crunching the 30 different sets of automotive surveys. 15 minutes on AYX, days and days on Excel, and without result by newbie hires just out of college.Either you believe it or you don't. There is a 132% annual expansion rate on the software, not because businesses like to waste money, but once it is in the door and gets used, it creates such delight and efficiencies that it spreads through department after department. The market is in the millions of seat - PERIOD. Prognostication is just that, prognostication. I am rather certain of this myself. There was also a recent survey done of corporate CIOs about what software they were thinking of looking at. The #1 software was not machine learning, AI, or any of that, it was analytics and analytic modeling. The #1 company mentioned was Tableau. I will leave it at that. There is no need to invest in AYX. If you think Excel will continue to dominate the world in taking in database sets, analyzing database sets, and sharing the results of database sets, organization wide, even with streaming real time IoT and machine learning data, then by all means, there is no need for AYX, so moving on.What AYX is doing, like almost all modern technologies are now doing, is democratizing data analysis, so that any person in the organization can receive and use the data that they need to better do their job. Again, I suggest reading the case studies. The ROI on the AYX product is incredible. It is not just the data "jocks" that need data. In fact they are the gate keepers, the kink in the hose of data analysis proliferating throughout the organization (like Mauser likes to speak about). My investment thesis is this product is superb, this product produces great ROI, there are millions of seats that will be sold, this company will probably at least quadruple revenues in the next 5 years (and profitably), and the degree to which the stock price will soar or not will depend on the uptake of new products, such as the streaming machine learning first mile product, and the communicating and distributing of result product that is the last mile. End to end product.In 2016 SAS had $3.2 billion in revenue. AYX will beat that.https://www.sas.com/en_us/news/press-releases/2017/january/2...Tinker
Duma,In the end all I can conclude is that you are trying to pull our chain here.Tinker
Duma,Data analytics is the end game of the New Paradigm. The completed finalized product. It is the competitive advantage. It’s what everything else is there to create. The IoT to collect the data points, the cloud and the storage and the databases to store and manage the data, the data prep software to make the data actionable, the processors to accelerate the compute, and finally the applications to turn it into intelligence. Remember the three pillars to be Big Data mega trend. Massive amounts of data (cloud, storage, network), advanced processing (gpu, FPGAs, tpu), and applications and algorithms(prep and analytics). Self driving car software is performing analytics on incoming data to determine what to do. An airline analyzes historical data and marketing dynamics to place the right airplane and crews on a route on a particular day and time, Amazon analyzes spending patterns to place a product in front of you while you’re scrolling, a business analyzes zettabytes of inventory and flow data to more efficiently manage product flows, another business analyzes productivity data to determine where to deploy resources or cut back. All of these things are data analytics and it’s huge money. This is what Alteryx (among others) does. Well they don’t build autonomous cars.$203B market by 2020.https://www.forbes.com/sites/gilpress/2017/01/20/6-predictio...IDC says that worldwide revenues for big data and business analytics will grow from $130.1 billion in 2016 to more than $203 billion in 2020.“Data monetization” will become a major source of revenues, as the world will create 180 zettabytes of data (or 180 trillion gigabytes) in 2025, up from less than 10 zettabytes in 2015There’s gold in them there mountains of dataThe increasing interest and investment in AI, in turn, will lead to the emergence of new tools for collecting and analyzing data and new enterprise roles and responsibilities. More than 85% of respondents report that their firms have started programs to create data-driven cultures, but only 37% report success thus farAYX has a product to help them succeed.In its much-quoted 2011 report on big data, the McKinsey Global Institute (MGI) quantified the coming shortage of data scientists (140,000 to 190,000 people with “deep analytical skills” in the U.S by 2018). Now they forecast that “millions of people” will be needed to serves as translator of the results of the work of data scientists to the rest of the organization.There’s your millions. I have Some TLND too. I’m going with a basket approach to the software, data, data prep part of the pillar. Lots of great companies doing great things and with very important roles to play. I can’t tell who will have the best performing stock so I won’t try.Darth
Simply for the sake of gathering 2 of the most effusively praiseful takes on Alteryx that I have come across, I will provide these 2 links within the same post, cross-posting them as replies both on the NPI board and Saul's board (along with another board or two on the paid side of Fooldom).An Alteryx take from Tinker from 5/25/2018 (other decent discussions within the thread.....despite its original topic being related to politics):http://boards.fool.com/this-hiatus-is-too-easy-33077297.aspx...Saul's initial announcement about starting a position in Alteryx from 12/12/2017, prompted in large part by an article from Bert Hochfield:http://boards.fool.com/a-new-full-position-1-32921051.aspx?s...Due to technical difficulty, this was put out in 5 parts, the above link is to part 1. Here is a later posting with all 5 parts consolidated into a single post:http://boards.fool.com/alteryx-write-up-all-in-one-place-329...Also, here is a thread where Saul pointed to Alteryx's customer video testimonials: http://boards.fool.com/alteryx-testimonials-32933548.aspx?so...volfan84long AYX
There’s your millions. I have Some TLND too. I’m going with a basket approach to the software, data, data prep part of the pillar. Lots of great companies doing great things and with very important roles to play. I can’t tell who will have the best performing stock so I won’t try.DarthDarth,With your basket approach, do you have any Appian? I'm not sure if they really have much of an advantage/moat over some of these others like Alteryx.
Small tidbit from the recent Pure Storage investor presentation (which may warrant its own thread......111 slides) that factors into the Alteryx discussion is on slide 6 here.https://s21.q4cdn.com/687136699/files/doc_presentations/2018...Only 0.5% of data is analyzed as of today. This seems to be a point of carryover between the investing theses for Pure and AYX.-volfan84----------------------(incorporating DreamerDad's quote method in conjunction with the italics to see if that might combo might catch on)---------------I think this 3.5 hour long video is what is paired with the slides, in case anyone has time to have it on in the background or watch the whole thing. Just takes a quick little registration.Link to the Investor Presentation:https://event.on24.com/wcc/r/1668204/8F67DEAC0A76CE015AB133D...
Who/what desperately needs this technology because they are burning countless hours a day wasted on Excel and DATA.I suspect the much bigger issue is how many issues are going unanalyzed because the analysis is beyond the Excel and whatever skills of the person with the question, who might be able to do the analysis with a tool like this. Of course, this is very hard to estimate.
I’ve been watching APPN. Haven’t delved to deeply. When I started looking at it the share price shot up so fast the risk/reward seemed to pass before I could get too into it and I haven’t looked too much in to them. I think that their performance and share price are a little closer on parity now. They’re worth a look, but a lot to choose from.On the data software/applications, so far. Some are more overweighted than others. I’m probably more diversified than many around here.AAXNAMZNAYXMDBNTNXSHOPTLNDTTDVEEVHey just got a notification that ABMD is joining the S&P 500. Nice!Darth
Duma,In the end all I can conclude is that you are trying to pull our chain here.TinkerHardly....but the reaction here is getting a little Tesla-like ;)Case reports are not that interesting from an adoption perspective Tinker.....you know that....every company can produce and promote case studies.We have subjected every meaningful stock prospect to an independent analysis/confirmation of its TAM/SAM.....you and others are arguing right past the question as though it is just a given and as Dreamer so impolitely stated, I dont have to convince you....I am researching this for me and whether I would take a position in this company......you already place your large bet.I think this article is a bit more balanced than what I am reading here:There is a great deal of data in that article (use your IPAd) on the analytics growth rate, on numerous competitors (there turns out to be many), and other items. But I found this referenced comments by an industry insider below of some interest (not for those who are already convinced that AYX has won the stock of the century award):https://seekingalpha.com/article/4167424-pure-play-self-serv...Author's Note: I work for one of the firms that currently competes with Alteryx and spent the last 5 years selling in the space and another 10 beyond that watching it.In my opinion, Alteryx of all the individual companies in this space, is in fact in the worst position. My opinion is informed on two key points.1. Go to Market Strategy2. Current TechnologyGo to Market StrategyMany of us in the space watched Alteryx over the last few years and wondered when Tableau was actually going to buy Alteryx. No company ever went out and purchased AYX on its own for is data prep needs, it was ALWAYS in conjunction with Tableau. As Tableau grew so did AYX. In fact, I don't think its that difficult of a point to make that AYX built a $2 billion valuation on creating Tableau Data Extracts.Things have changed dramatically for AYX in the past year. Instead of purchasing AYX, Tableau built its own home-grown data prep tool in Tableau Prep. I really don't believe the market has fully baked in how significant an existential threat this is to AYX's long-term viability and health. Yes, many companies have 100s of AYX pipelines they have created in order to build TDEs and get their work done, but with Prep being offered for free to existing Tableau clients - clients will kick the tires of the new tool and likely begin new projects in Tableau Prep and begin transitioning older projects as needed. This will curb further revenue growth potential for AYX.We won't see a significant drop in total company revenue streams immediately, but the canary in the coal mine will be net-new revenue and logos. I suspect will see a significant fall in these in next 12 months as new clients for Tableau will focus on building with Prep instead of AYX. The flipside will be the S&S stream will be more viable and durable. That's good news for AYX because it gives the company runway in order to correct for the market.The market and where the puck is going is changing dramatically and is highly fragmented. New growth is going to come from AI an Data Science applications. That's a problem for AYX.2. TechnologyThe dirty secret of AYX is that the technology under the hood is still client-side based and not especially scaleable. AYX was the perfect companion tool to Tableau Desktop as both worked on smaller, local datasets. In the case of AYX, as the dataset sizes grew this became more glaring. Enterprise datasets have been making their way to Hadoop into Data Lakes for cost savings while the AYX has not kept up in this area. To get an idea of what's happening here go check out this.http://bit.ly/2juR8T4Apache Spark is the coin of the realm at the moment in data science and as customers are beginning to make deeper investments in data science and this SHOULD be the next great growth area for Alteryx. Go out and compare this to other tools from IBM, Dataiku, DataRobot, and Domino. Its not especially intuitive for those who are more from a point-and-click interface see IBM SPSS Modeler, Dataiku and DataRobot nor the power from a coding perspective of say a Domino. In fact what should be the biggest Go-to-Market partner for AYX in Data Science, Tableau, is actually not even promoting AYX for those workloads, Tableau is promoting DataRobot. Tableau reps are being comped on DataRobot sales. To put it another way, Tableau is pitching itself as the Data Prep and Visualization on top of DataRobot data science. Looking around, the AYX tech in DS is behind competitors and AYX doesn't seem to have a friend in the world.ConclusionDoes this mean AYX is a bad short-term bet or is going to zero? No. It does however mean that their are serious curbs and governors on how much growth the company will achieve. I might even put a pair trade on with Tableau shorting AYX and longing Tableau as I believe the distance and correlation of these two companies are going to diverge over the next 2 years as they de-link from each other and AYX starts feeling the head winds of no longer being able to count on Tableau for new logos and the data science space competition becomes more intense.I can only conclude that you are trying to pull my chain by not considering these and many other issues with AYX. I would expect this behavior from Dreamer.....but not necessarily from you.
Duma,I read that piece and it was, for you New Yorkers cover your eyes, pigeon crap.it is written by a competitor, and this person is focusing on document prep! Document prep is ancillary to what AYX does. This is the third time I have said it. It is ancillary and not a core function. Whereas Tableau does not have an analysis engine, which is AYX's core product.Thus, if one wants to run analysis, and is using AYX, one will not use Tableau's data prep program (even if using Tableau) because AYX's program is superior anyways.If one is not using AYX as the analysis machine, and one wants to run analysis and send the data for visualization to Tableau, one might use the Tableau product for data prep, then use the data to run it through Excel or whatever other program they are using, and then send the results to Tableau for analysis.Statistically, only 15% of the analysis coming out of Designer by AYX ever goes to ANY visualization program at all! Much less 100% to Tableau. That makes a quite distinct minority of analysis runs that ever go to Tableau, and why would anyone buy Tableaus' document prep program unless they were going to send the data to Tableau for visualization thereafter.Data prep, free or not is a complete and utter red herring spit out by someone who is competing against and trying to get business vs. AYX.This is the third time I have articulated this in two days. If this guy was actually articulating something that was material, then that is a different matter. But his focus on data prep is complete hog wash. Whether it is free or not free. If the above does not answer your question, I have no more to contribute to it, as yes, I have read the article you linked to, I have gone deep and wide looking at things, and frankly I went from someone, like you, who really didn't feel all that strongly about it to becoming quite enthused about the investment (and investment I initially made simply for a shooter term bounce and not a longer term holding per se).Tinker
<<<No company ever went out and purchased AYX on its own for its data prep needs, it was ALWAYS in conjunction with Tableau.>>>From the top of the quote you cited, if less than 15% of any output from Designer ever goes to any visualization program at all, then how the heck are purchases being made for the vast majority of users who will never use a visualization program?Further, Tableau just released its data preparation program. Just this past month! It is free for the first year and then $800 a year thereafter. So, my witness (as I will put my lawyerly cap on - which is basically my paid hobby these days it appears) if Tableau had no data preparation functionality until this just released miracle product that they will give away for free for the first year...then how did anyone go out and by Designer without Tableau's data prep functionality THAT DID NOT EVEN EXIST ON THE MARKET UNTIL THIS PAST MONTH!No, I would probably just be low key with it, put up a simple graphic, and then quietly sit down and allow you to answer that question. Next witness.Tinker
https://www.alteryx.com/solutions/big-data-analyticsAlteryx pushes down Big Data analytics processing to Amazon Redshift, Apache Hive, Cloudera Impala, Microsoft (Azure SQL Data Warehouse, SQL Database, SQL Server), SAP HANA, IBM Netezza, Teradata, Spark, and Oracle to analyze more, faster.Ummm, yeah. Lots of credibility that author has. Not up to snuff for big data loads. Well, it does not pretend to be because it has APIs (just like everyone else) to third party applications, and when this Big Data is so processed, AYX is used to provide the analysis of the data.Did this author, at all, even talk about data analysis? I mean that is the core of what AYX does. It is absent for the most part in what Tableau does.But I do not need to monopolize the floor. The author is either someone who does not know what he is talking about, has just enough information to be dangerous, is trying to short the stock, or is trying to put out rumors to make his sales job easier. I think all of the above.Tinker
Btw/ Designer enables the examination of petabytes of data by these services without (1) the data ever leaving the database, and (2) without the need for programming, or some math or data jock to do it.Let me know another tool that does that.I am resting here. It is not even necessary to go any further with this author as you can see exactly where is coming from.Tinker
Tinker:Not trying to convince you of anything. That was NOT the author BTW....it was a contributor that seemed to have experience in this field.The author of article brings up several other deficiencies in Alteryx if you care to read them but suffice to say, it is a far more balanced article.
how hard is it to use Talend?https://www.quora.com/How-hard-is-it-to-use-Talend depends on what you call "hard" but not super difficult how good is the open source formhttps://www.quora.com/What-is-the-commercial-license-cost-of...Open source version has 800+ connectors which solves out task of handling massive data very easily and also creates a platform independent code in Java. But the commercial version of Talend provides broader enterprise features including team collaboration, improved management, monitoring and support from Talend team. https://www.quora.com/search?q=how+good+is+the+open+ut+ice+t...apparently the free form is pretty good so one can wonder whether the commercial form offers enough to make it worth paying for unless you are a large enterprise.https://vimeo.com/196848038 may answer that- support and integration less hackingTalend customers report that the Talend commercial edition pays for itself in a few months through productivity gains, cost avoidance, and revenue enhancement. When your team works faster, spends less time on maintenance, and efficiently shares their work, you reap the rewards. It's a valid question to ask how Talend is going to make money. I think the potential demand is huge but they will have to make the paid version lots better than the free version. The more they grow the more resources they can put to that task. Work sharing could be a key.
One has to be careful about the term "analysis". Sometimes it means computing something out of the data that is not there in the data itself, like a ratio or a correlation or a regression. But, sometimes it can also mean just presenting the data in a way that us humans can see the relationship, like plotting one thing against another so that one sees the connection, even without the math.It makes me wonder if any current analytic tools have a function like we used to use in grad school called the "Churchill program" (no idea of the origin of the name). This would take a data set and compute empirical correlations between all of the data items, the compute a regression between each data item and the two other data items most correlated with it, and then report any data where the observed value was beyond a certain parameterized limit from the value predicted by the regression. The idea was to highlight data items which were to be double checked for possible data entry or other errors. But, the discovery process of what was correlated to what was itself a powerful input to analysis.
Okay, now that I had a bike work out feeling less grouchy. Sorry Duma.Now Tamhas, we had regression models back at Duke using a plug in with Excel. Quite sophisticateded. So sophisticated that I know what they mean but forgot how to do them. One student, very persuasively, figured out how to justify paying a short stop $17 million a year in 1999 dollars and making the owner think he was getting a bargain.Designer has 172 or so functions built into it. On top of that you can code, and you can plug in third party apps, such as I showed with Apache or the like.With this most anything you can think of should be covered. And if not, that is what the data jocks are for. They can code, put it on the server, put out a memo as to how and why to use it, and then the function is distributed to everyone to use in the company. Thus analysis, even very sophisticated analysis is diffused through the organization, and repeatable, and in form that is easy to train any new employee. Good stuff.I mean, I am looking for bad stuff. Have not found it yet. I will continue to look, and take a look at the article Duma is referring to again. What I remember from it, is that same comment by the industry salesman. As with so many such things, it was other pigeon crap, but I do look at the comments and sometimes find interesting stuff that is honest and informed. But much more often some short or enemy of the company putting stuff like that out. Usually pretty easy to spot.Now lets see if NVDA GPUs get taken out by AMZN, MSFT, and Google home spun ASICs, never mind that no one wants to be locked in, and no one wants to have to learn how to program on a system that is a silo attached to one cloud, etc. But you know, Amazon will take out Nvidia as well, so will AMD and Intel, and some third party (not yet known) because every one has done so well so far except Nvidia, who also has the largest AI budget in the world, and is the heaviest users of AI in the world as well (although a case for Google can also be made there, but Google is not focusing all its AI efforts on building chips and systems as NVidia is).AYX is certainly an easier target, but with much more growth potential (maybe as Nvidia...) but none of the negative talk has as of yet had any basis in reality.Tinker
Watch out for those neuromorphic, quantum computing chips, Tinker.
Duma,I have read through more than half of the article and will resume again. Well written and unbiased article. It lists all the competitors, strengths, weaknesses, et al. None, that is NONE of the competitors offers the ease of use, short learning curve, no coding, etc. that Alteryx offers with Design, and unlike said commenter, Alteryx is used to analyze and transpose data sets that are 200 million documents large or larger, and of course I pointed to APIs seamlessly and without code linking to cloud services for faster processing of even larger jobs.Look under figure 2 in the article. Unfortunately, on my iPad Pro I am not able to cut and paste as I might be able to on my Mac (but I am not a member on my MAC, only on my iPads) so you will have to go back and look. There is the complete description of what separates AYX from everyone else. Talking 80% increases in efficiencies, jobs that take hours, days, months, are done in minutes, hours, days. It frees up people to handle more complex tasks through automation, has a very low learning curve, short time to implement, etc. It is also not mentioned there, stable, well written, modern code, etc. Basically everything I stated, and there is not a single piece of software out there (perhaps except from some of these micro vendors, who knows) that have these very important and very critical attributes. That is what makes AYX. A very sophisticated tool that real data scientists love to use, and yet can be used for sophisticated modeling and multiple other issues by people untrained in the data sciences, that are able to get up to speed within hours, and I am sure it is not that difficult to train them on the basic concepts they need to analyze data for their jobs. And this is especially critical since there simply are not enough real data people around who can handle all this, and the ones that are, are quite expensive and you don’t want to waste their time.SAP is interesting. SAP has taken a very good cloud approach, through Cloud Foundry for one thing, but also in its data analysis. But SAP, as it is with everything, is very expensive and made only for the very top of the line installation and usages. I doubt there would be much cross over at all. SAS uses its proprietary language you need for coding. IBM is well, IBM, and they want to move their service team in (you don’t need a service team with AYX). DATA has a great product, its new software release is very light on substance, and it has practically zero of the sophistication that AYX has for analysis. No way Tableau catches up there, and either Tableau buys AYX or vice versa, or someone else does.The article, unlike the commenter you referenced, is quite positive on AYX. The author simply did not like the valuation, which is a frequent issue with writers on the service, they love the company, hate the valuation. Except for Burt of course, who only sometimes hates the valuation, like with Arista, and he really did not take well to Pivotal, but unlike Burt, he really did not get Pivotal at all and I think he reflexively wrote about them without the context or knowledge he normally puts forward.Anyway, no, the article itself, well written, does not really come up with negatives about AYX. It properly puts AYX in context, as the sole such software company in the world that has made a very sophisticated tool that even the highest level data scientists appear to love, that can be used down the chain to even first year analysts with no coding and very little statistical experience, that produces incredible ROI and efficiencies that heretofore were not available in the world.That ain’t a bad place to be product wise. Also, AYX’s marketshare is currently so low that it is not really profitable for the big players like Microsoft or SAP or IBM to go full out and try to produce a similar user friendly sophisticated product. It would barely move a decimal point in the Excel spreadsheets used by the executives to try to make such a move. So by simply being small enough for now, they should have a few years of little to no real competition, and by the time they get large enough for it to matter, they will be large enough for it to not matter anymore in regard to new competitive entries into the market.I will continue perusing for negatives however.Tinker
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