Name: What’s New: Spotfire® 14.6 unveiled - Turning data into decisions with reference elements, and smarter visualizations
Uploaded: 2025-10-16T16:16:12.705Z
Duration: 55 min 23 s
Description: What’s New: Spotfire® 14.6 unveiled - Turning data into decisions with reference elements, and smarter visualizations

Transcript for "What’s New: Spotfire® 14.6 unveiled - Turning data into decisions with reference elements, and smarter visualizations": Hello, everyone, and welcome to today's webinar. What's new? Spotify 14.6 unveiled, turning data into decisions with reference elements and smarter visualizations. We're thrilled to have you with us today. I'm JP Richard Charman, and I'll be your host for this session. Now before we get started, I just wanted to cover a few housekeeping items to ensure you have the best experience. Now the webinar will last for up to around forty five minutes with a q and a, segment at the end that will be held at the very end of the presentation. Now if you have any questions during the presentation, please do not hesitate to use the q and a panel located on the right side of your screen, and we'll address as many questions as we can during the q and a segment at the end. We've also made a few assets linked to today's webinar available in the doc section of your webinar platform. So that's located right in between the chat and the q and a function in the webinar platform. So please do feel free to access these at any point. After today's session, a recording of today's webinar will be made available on demand, and we'll email you a link to the on demand version very shortly after the event. Now with that, let's dive in. I'm excited to introduce our presenter today, Arnoux Varin, our principal product manager here at Spotfire. And with that, I'll hand it over to you, Arnoux. Thank you, JP. Hello, everyone. I'm Arnaud Varin, part of the Spotfire product management team, specifically focusing on visual analytics, data management, capabilities of Spotfire, and I'm very excited and happy to present you today with, next, major release for Spotfire. Before diving into the details, let's just give you a few words about Spotfire. What is Spotfire? Spotfire is the visual data science platform that makes smart people smarter by this combination of advanced analytics and industry specific visualizations that you can use to solve complex business, complex industry problems. Our vision for Spotfire is based on three main pillars. First, visual driven analytics, and that's have been the case since Spotfire exists. It's about supporting the iterative nature of data discovery through tight coupling of visuals and advanced analytics. That's what Spotfire was made for. That's how Spotfire differentiates from other tools in the market by this interactive, data discovery, aspect. Second pillar is a focus on industry. It's about making sure that Spotfire can solve the most complex domain specific industry data problems with unique domain specific visualizations, algorithms, and data connectivity. I'm very happy that we have been able to deliver in this aspect in the last few months. You will see some of that today. Third pillar, enterprise scale. That's not a new pillar for us, but it's about making sure our platform is, current, secure, governed, and extensible to advance the needs of thousands of users with a wide range of use cases and data science data sciences. So it's a focus on the enterprise and making sure that analytics operations scale at the enterprise level. Few words about our the Spotfire platform and our offering. In 2025, we drastically reduced the number of Spotfire products to make our platform more comprehensive and also more accessible. We simplified our offering quite a lot into three main products. First, we spot fire analytics. This is the spot fire you know, and all customers have access to these capabilities. It offers interactive visual analytics to explore and understand data and build advanced analytics applications with high receive visuals, visual data wrangling, powerful geo analytics, AI powered recommendations, and advanced analytics built in. That's the Spot failure you know of. Second, Spotfire data science, which is a completely new offering we are we we launched earlier this year that extends Spotfire analytics with domain specific tools, workflows, machine learning, and modeling designed for energy, manufacturing, and life science. And Spotfire Data Science includes all the functionalities of Spotfire Analytics and STATISTICA. Yes. All the power of STATISTICA is included with the Spotfire data science license. Then we have Spotfire Enterprise for our large customers who need collaboration across teams, and we need to scale their analytic operations with robust security, governance, and efficiency. Spotfire enterprise includes Spotfire servers, Spotfire automation services, Spotfire statistics services, Spotfire consumers, Spotfire statistic server, and more. It bundles all the Spotfire and Spotfire server components into one product. And in this presentation today, we will focus on our three main products, Spotfire analytics, Spotfire data science, and Spotfire enterprise. Before I dig into what's new, I just wanted to give a few words on our release cycle that we updated recently. We have two release train or two release tracks for Spotfire. LTS, long term support release that we release typically every eighteen to twenty four months. Deal releases are maintained for eighteen months after the next LGS release, and they are supported for four years. To give an example, the latest LGS, Portria 14 o, will be maintained eighteen eighteen months after 14 six LGS will be released, and that will happen anytime now. In parallel, we have innovation releases, which are much more frequent that will release typically every quarter, and they are they are maintained until a new innovation version is available, and they are supported for one year. So the latest innovation release, 14 five, that was released earlier this summer will be maintained until 14.6 is released. Alright. Let's now look at what's new. Spotware 14.6 LTS is our next long term support release. It will be available this month at any time now. That's a big release. If you if you go back to the last, Spotfire LTS release, Spotfire 14 o LTS, which was released about, twenty four months ago, Spotfire 14 six LTS is more than a 110 new features and enhancements for you, and it implements and solve more than 90 user IDs. User IDs are IDs posted by our users in the Spotfire IDs portal where you can go to suggest enhancements, new features, and votes or, features as well. I really encourage you to use the Encoded Data IDs portal. Us as product manager, that's a great, great source of information to know, to take into account when we prioritize our road maps and future developments. So with that and with 14 six LTS, you see that we take ideas seriously, and we deliver on them. So please continue posting great ideas. So Spotfire 14 six LTS with lots of new features and ID solves. I think it marks a major milestone for Spotfire innovation and stability at scale. But what's also really important is that innovation doesn't stop at the release. Now users can discover and install new visualizations and actions directly in Spotfire without having to upgrade the platform. This means faster access to new capabilities, and admins stay fully in control. Add ons and domain specific demos are published and updated between releases, giving users access to fresh capabilities as soon as they are ready. And we also deliver data functions and core updates to Spotfire through through regular service packs, ensuring continuous evolution with enterprise stability. So Spotfire, starting now, isn't just a product with big releases. It's a living platform that keeps growing between them. For what's new in Spotfire 14 six, I will have I will focus on four topics. First, Spotfire data science, industry visuals, and domain specific visualizations. Then I will move to Spotfire analytics, smarter, clearer, more flexible analytics in Spotfire 14 six. I will have a quick look at what's new in Spotfire Copilot, our AI extension for Spotfire. And then I will look at the admin side and the the platform side where we are we are simplifying administrative, and enterprise scale deployment for Spotfire Area. And at the end, if you have any questions, we'll we'll have some time hopefully for for q and a. Let's start with Spotfire Data Science. For who is Spotfire Data Science? Spotfire Data Science empowers process and yield engineers to run SPC, quality control at scale with control limits, specification bands, and domain specific metrics applied across tools and lines. With particular data science, engineers can visually detect anomalies, optimize tool performance, and reduce scrap, accelerating root code analytics when issues arise and revealing subtle variations, driving yield improvements and sustainable production goals. For the energy sectors, Spotfire data data science helped engineers optimize well spacing patterns and identified in field opportunities to ensure every field development investment delivers maximum return on investment. Once wells are producing, it enables continuous monitoring of performance against targets, benchmarks, and regulatory threshold. Trends and drift are spotted before they impact the output, and hidden variations in production become visible to guide better decisions. So Spotfire 14.6 LTS is our first long term support release to include Spotfire on data science, a new Spotfire product that we introduced earlier this year that is designed for engineers, scientists, and subject matter experts and that combines all the functionalities and capabilities of software analytics with powerful industry visualizations and domain specific data science functions for deeper insights across energy, manufacturing, life science, and other complex industries. With Spotfire 14.6, we are extending Spotfire data science with foundational new features such as, reference elements. I will speak more about it later. For threshold and ranges, match on column names, for metadata metadata driven analytics, violin plots for research statistical exploration. And this addition in addition to all the value we delivered since '19, Postgres Data Science 14 point five during the summer, makes Postgres Data Data Science more powerful and flexible while ensuring scalability for future development. Right? So just a reminder on what we delivered starting in '19. I mentioned STATISTICA. STATISTICA is part of the Spotfire data science product. When you have a Studio Data Science license, you have access to the STATISTICA. We introduced the add ons browsers. So right from Spotfire, you can access through visualization, actions, add ons, without leaving Spotfire. We are adding diff we have been adding multiple data functions built in the product that include spatial functions, missing data analysis, time series, manipulation functions available built in. Time series preprocessing, I mentioned that, and very specific visualizations, domain specific visualizations. I'm I'm thinking well well well well well well well well well well well well well, Let's look at what's new in 14 six. In 14 six, you will be able to enrich visualizations with data driven lines, bends, areas, boxes, markers for providing additional context, benchmark, and insight right within your visualizations. You'll be able to place targets, controls, specification limits, acceptance ranges, that you source from either static values, from expressions, or from separate data tables. So your visuals can stay in sync as the rules change. And the reference elements adapt, to group your data and series by splitting the data by or by category or by color. They are fully stylable as well. With reference elements, you can add limits and targets in the form of lines in visuals, for instance, to show specification and control limits or goals, as horizontal or vertical lines or tool, line, or segment. You can display acceptable ranges in the form of bands or areas or boxes in visualizations. For instance, it could be shaded regions between lower or upper bounds, to visualize past fade windows. You can display, windows of interest in the form of boxes at twilight intervals, like shifts, outages, maintenance, or value windows. And you can also add reference markers in visuals as well, such as benchmark or trends anchors. So you can pin, for instance, margins or averages or other types of aggregates and connect them to reveal drift directly. A few example of use case that we have been observing for reference element, if I take manufacturing, process stability, you can apply three sigma control limits, specification banes, and twilight shift of outages, directly in your production charts. Yield analysis as well where you can overlay wafer level threshold, acceptance syringe, benchmark, and really very quickly identify variations across your lots or or your wafers, applicability in energy as well for production operations or drilling, reservoir studies. By adding more context to your data and adding a context that allows you to compare your measures with rules or with specifications. I'll show you a demo of reference elements after the slides. Related to reference element, a new column matching options that we are adding in 14 six allows you to actually make it very easy to connect tall data tables with wide data tables. Tall data tables could contain parameters, metadata, of tools or machines, for instance, and wide data tables often contains, a set of measurements with a lot of of columns. Right? Could be temperature or pressure or flow. And so one of the the issue was often to connect these two tables. So you had to go through pivoting and pivoting the data, and that's something I believe we are solving here. That's specifically useful for reference element scenarios where, business rules, targets, threshold are are defined in auxiliary tables while raw measurements come in wide tables with many columns. And so we are adding a new way, to match columns between these two type of data. I'll I'll show you also a demo on this. We are making a lot of enhancement to the box plot in Spotfire we are 14 six starting with, the ability to display violin plots directly in box plot to reveal full probability density distribution, around each book each box to survey to surface skewness, multimodality, or hidden variations not visible necessarily, with quartiles and regions. So bioin plots, inbox plots are they are valuable, for instance, in process engineering to understand variations in yield and and defect rates, in quality analysis or reservoir engineering as well to explore performance, beyond the summary statistics. We are adding a specialized visualization as a particular data science add on, which is called the statistical funnel plot. That's a specialized scatter plot that overlays 9599.9% control limits, to compare rates, fairly across different volumes. The goal is to separate common cause noise from special cause outliers. And this visualization is available as a spot for your data science visualization add on from the add on browser I was mentioning just before. Another new visualization, the par plot, which is very specialized, to visualize data in a circular coordinate system. It supports lines, markers, areas. And the goal here is to plot asymmetry or or to measure depths to reveal, for instance, wellbore trajectories and reading, directionality, in upstream. So this, again, is available, as a Spotter data science add on for Spotfire in the add on browser. We are adding a connector for loading well logged data directly from Spotfire into Spotter AR from last files. That's also available as a spot.io data science connector. And this is used then to feed well known visualizations that we are also have available as part of spot.io data science. And we are adding also a connector for accessing and loading spatial data from s three sources directly into Spassayo. So now with the s three connector, you can connect to local file based GIS databases, GB, GDB files, or you can connect to ArcGIS online or to ArcGIS enterprise deployments and bring the data into memory directly to Powerworks Spotware visualizations. EDS three connector is available as a Spotware data science connector add on as well. Last thing, we are I mentioned at the beginning new built in data functions for Spotfire, spatial functions, missing data functions, time series functions. In Spotfire 14, six LTS. We are improving their usability and their flexibility to make it much easier to configure, reuse, and to and to apply advanced transformations. Different improvements, we we made. Streamlined, the the parameter ending, so the input parameter when you configure, when you configure a data function. You can also pin data functions in the function in the FX fly out now, so you can have a a much quicker access. We also have some improvement when it comes to coordinate system transformations where we we are making the setup of these transformations functions much easier. Now looking at Spotfire analytics, we had a lot of new capabilities since 14 o. I tried to summarize the key new capabilities, for '14 in this slide here. We are introducing a completely new visualization of Toring experience. That's something we started developing a while back and that we have been delivering, iteratively, and we have made great progress. And by the way, with this new experience, it allows us to provide two web authors new visualizations, for instance, like the box plots, which is now available on the web on the web client. We have we have been making a lot of efforts to modernize our user experience and make feature that were previously only available to Windows user, now available to all users. I'm thinking, for instance, data tables relations. We have brand new data tables data tables relations graph available straight from the data canvas and available to all users, WebAuthors included. Document properties, filtering scans, both are now available to WebAuthors as well, with a completely new experience that lets you see where document properties are are being used through a Spotfire within a Spotfire applications. And, same for filter schemes, where does this filter scheme is being used in my analysis. We are adding support for engineering notation formats. We are adding we have been adding in 04/2005, so now available in 14 point six eight years support for custom marker shapes, which means that you can now import your own iconography and images and use that in maps and scatter plots. And not only you can use your own images in maps and scatter plots, you can also build, marker shaped collections. So if you have, for instance, company specific iconography or logos, you can build collections, save collections in the Spotfire library and reuse them throughout your teams. That's an an example here of custom custom markers. In terms of visualizations, we have been continuing delivering visualizations on a regular cadence. I can mention the Maricos Marimeco chart, process diagram, milestone diagram, a circular bar chart, organization chart, all available as add ons for portfolio analytics. We have been making improvements also to, jobs automations where you can now, for instance, create a job to automate the distribution of a report, but not only automate the distribution of a report, but also, personalize the report based on the recipients. So you can now have a single Spotfire analysis and send this analysis as a report to different recipients who will see different datasets based on their profile. When it comes to automations, we are also adding the ability to loop and to add scripts. So it allows to do quite complex data science, workflows. For instance, you could have an automation job that launch a software analysis, run a first data function to do some data cleansing, run another data function to do some prediction, and then create visualization. And then as with every Spotfire releases and since Fortino, we have been continuously modernizing our data connectors, adding web UI's, meaning ability to configure them from the web client, and also adding single sign in capabilities with OAuth support and OpenID connect support. Let me present you what's new in '20. I was talking about box plot before. We are continuing with box plot and making box plots more flexible. Box plot with platform 14 six can now be displayed horizontally. The goal is to improve the visibility when you're working with long category labels or, with a a limited vertical space. It solves it's, yeah, it's the the goal here is to be to enable you to to to display long category names, which we know it happens quite a lot, especially, in semiconductor manufacturing, where you you may have long wafer wafer categories, for instance. In the same sense, we are adding support for, x axis display in the box plot and support to display the x axis labels, as vertical, in the box plot. Same goal is to enable you to show the full, the full category names, and don't lose the context. One more improvement enhancement we are making to the box plot, we are allowing you to write your own expressions, your own measures in the statistical tables. So in addition to the statistics measures we provide out of the box that you can add to the statistical, table in the box, but you can add your own now by writing your own expressions. I mentioned the new authoring visualization authoring pile. For people who don't know what it is, this is how it looks. It's a much more modern experience to configure visualization, a consistent design with the same layout across all visualization types. You have you can use search to find what you need instantly. You can configure multiple visualization at once. So you can now select multiple visualizations, configure axes of multiple visualizations at the same time, drag and drop properties, sync properties between visualizations, meaning that if you do a change in one visualization, it will apply automatically to all the synced synced visualizations. And in '14 six, we are adding the ability to undock the panel and move it around, the UI if you prefer than having it on the side, of Spotfire. We think this new experience, we see this as a foundation. It is still not the default experience in Spotfire, but we expect to move it to the default experience, fairly soon. So now you still have the the experience you're used to, but you can switch to the new experience and trade out. We are making we are also making some improvements on the authoring column, especially on the column, print properties. Authoring from the data in analysis panel here, you can now multiselect columns and, change the formatting of multiple columns at once. We are making also properties controls much more scalable. We know that in some case, when you have when you when you use properties controls, for instance, to select columns and drive visualizations, we had this limitation of a thousand entry in robotics control. This limitation is no more, and so list box drop down sliders can now display thousands of value, with no cutoff. In 14 six l c s, you will see a brand new welcome page as well, which replaced the static start screen that we had. And the goal here is to be able to inform our users, highlighting, news about the product, new trainings, new webinars, community updates, and ensure our user community is aware of what's new, in Spotfire and on its capabilities. That's a dynamic welcome page available in 14.6 LTS. I mentioned modernization of our connectors. That's true also for 14.6 LTS where we are modernizing our vertical connectors, modernized experience, consistent across desktop and web clients, support for single sign on, and updated reports, for our audio connectors with support from the latest ODBC driver. Without going fur before going further, I suggest I do a quick demo. I want to show you, box plot enhancements and what are reference elements. So let me switch to that. Okay. Oops. What are you shooting here? Okay. Let me check that you see the right screen. Yes. Okay. So here I have I just want I start with a with a pretty simple dataset, where you see some, yeah, some tools parameters. I have I have data over time with the production line, product family, and some parameters here in this case, temperature and pressure. Out of this dataset, I created a very simple box plot. And I want to before going through reference elements, I will show you what's new on on the box plot and some of some of the new capabilities. First thing we are adding, and it's, from the the statistic table here. You see you can add measures. So you can either add measure that are that are built in the product or you can type now your own. So I can add standard deviation, for instance. Give it a name and boom. That's the way I add custom measures in the statistics table that can show the formatting. So now this is this this is a very simple expression, but you can use your own explain if you have custom KPIs that you use internally. You can write pretty complex expression and display this information as as a statistical measures. I mentioned the the violin. So you see and, actually, by the way, at at the same time, you see the new visualization properties experience. The main difference here is that I don't see all the properties. I just add the properties I'm interested in. And here, what I want to add is the density distribution. So I just add the violin, and boom. Just like that, I have a violin layer that is added to my visualization. And you can you have the end on, what method to use to compute the violin. If you're used to display histograms, in box plot, both works great together and they look great together. The the box plot gets split. If I remove the violin, then we don't we just display the histogram as you're used to. What else? Yeah. We are also let me check. We are also adding support for displaying labels in the in the box put access labels. Let me remove remove the statistics table. So before you were you before that, before '20, you would have to use the statistic table to to be used as the x axis, labels. Now we are adding to show labels in the box plot, and we are adding the ability to show the labels vertically. That's what I was telling you before. And the last enhancement we are making to the box plot is the horizontal orientation. You just go to the appearance tab here and choose to display the box plot horizontally if you prefer this way. Let me move it back to this. Yeah. So that's these are the enhancements we are making to the box plot, expression based statistic table, density distribution with the violin plot, x axis scales labels, and vertical orientation of the labels, and horizontal orientation of the box plot. Now now now that we've explored, the new box plot capabilities, I want to move to what I believe is the highlight of Spotfire 14 six, reference element. So in this case, starting with this box plot, what I want to show is a trend line over this box plot. So you see now next to the visualization title, I have a plus button. If I click the plus button, it allows me to add what we call a reference layer. So I would just click this. By default, when you add a reference layer, we display the average of the y axis, information here by category. Here, what I want to create is a trend line based on the median and the median value. So I'm just changing the expression to median. Alright. And you see that my lines change. And I don't want to display lines, so I remove lines. And I have a set of of options to build my reference layer. I can display markers, lines, box, bands. I will show you all of that. I will first add markers. So here, I'm adding markers for each median value for each box plot. I can choose the shape, either choose a default shape, or leverage the new capabilities we introduced earlier this year with a custom markup shape capability. You see here I have a set of, I have different collections that I could pick from. Let's let's stick to the default shape here. So I can choose the shape, define the markup size, a color. Then I want to add maybe the median value, so a label to this. I can choose how to display the label, the alignment, the here, align to the top, the direction, the font settings as well. I will keep it like this. And the only thing that I need to add now to build my trend line is just to add a line connection. And just like that, I can style my line, switch a bit the width, switch the color, and just like that, I build a trend line on the box plot. That's just a quick example of a reference element. So here I'm adding a reference element to a box plot, and I'm building and displaying markers and creating a connection between these markers to display as a trend line. And like I was saying in my presentation, it's work fully working with color by, trend is by. So, yeah, in this case, I'm displaying, the site. It's the same box plot with the same information, but I color by production line. And I also have created a trend line for each production line. We have three trend lines. I will show you another example. Alright. Now in this next example, we'll continue exploring reference elements. This time the in this time, I will focus on how you can use the reference element to visualize control and specification limits, for process data. So here I have quite the same datasets, but I have two data table. On the left, I have a data table saying over for some tools, information, and some process metrics over over over time. And I have two specifications and control units in a separate data table. I will directly switch to the final visualization. Here you see. This is what you can do. So first, you can add here a control limits view. This is these are the lines in red that you based on my two limits data table. I just select upper control limit or lower control limit and display a secondary value for my lower control limits here and display these as lines. These are my two lines. And I added a second reference element, which is for my specification limits. So it's quite the same. It's two lines between primary value here with my upper specification, the lower specification at the bottom. And the difference here between the two is that in addition to simply show two lines, upper and lower, and coloring and shading shading, the area between the two here in green just by adding a band. That I where I can choose, the field color. I can choose to display border. I can choose also to display here in the appearance how to display the event. Could be in foreground, background, the the the the the span eventually, but in this case, it's not relevant because it's in Trellis. So that's yet another another example of how you can use reference elements to display your control and specification limits. And since both of these reference layers depends on metadata data table. Every time that, specs specification update, they are directly reflected in this type of visual. And you see it here in I mean, for this example, you directly see what data is below or above, or or above your specifications or. Two other examples really for for inspiration. Here I can provide, this is a line chart. And in this case, we draw two lines. So two, you see, two two reference lay one reference layer with two lines and a band based on the calculation. I think how the calculation I'm using is based on the three sigma calculation. So you display a primary value as a as a top line, a second bar value as the the the the the below lines, and you just display this as a band with a color field in in gray and a a border that you see in darker gray right here. Another example I can provide here is combining raw data with aggregated data view. Here in this case, we have a scatter plot that represents, the raw data points. And on top of it, we layer a box plot, that is built with reference element. And you retrieve all the the all the the elements that constitute a box plot. So it's it shows it's a way to show, to combine a detailed data view, like a scatter plot, with, aggregate data within the same visual. So you have the sun the box plot here that summarize the distribution and highlights outliers and the scatter plot that shows all individual data points here. That's something that we've we've heard, many requests, especially in life science and and semiconductors. And I will switch back to my last demo. There. Okay. So this is, this is to show you how I mentioned match on column names before. You know, we have columns, column matching, column functionality for quite a while to to link two data tables together in visuals, and we are improving this, in Spotfire three forty six. So here in this in this example, I have two data tables. I have a wide data table that contains 30 or more data columns with parameters measures, and I I have a limit that, which contains for each parameter, some specification limits or control limits. If I switch to my next page here, I will show the same. I I use my parameter data table here to interact with this histogram. We are using the probably unknown feature, but using the column format here. You can use column format to to drive visualization. So based on the column the whole selection here, I'm driving directly, the axis selection right here and which column value to display. You see, since I switch parameter, the the the data change. And this is done using the columns from mark, functionality that we have from quite some time, but I believe it is very powerful. Now I want to display limits on this histogram, and I have prepared a reference, element group that is hidden and that I will unhide. And now you see, similar than what we showed before, you see limits, control limits, and specification limits. But the problem here is is that there is no way to link, between these limits and the parameter that I choose. They do not change. So let me show you what we did to to to specify, let's say, this issue. Now the only thing I have to do is to go to data table matching, and you see it tells me there is no match for the limits. I just click add match. On the left data table, I keep it to column names, and this option is actually what we are having in 14 six. And in the right table, I simply choose parameter and click okay. And now I'm done. We have the column matching set. There is no need to do to to do any pivot or unpiboting of the data. Just match the based on on the column names. And now I can display control limits, specifically efficient limits for each parameter that I selected using the column from mark, capability. That's what I wanted to show you, for my demos. Let me switch back to my slide deck. Just a few words on Spotfire Copilot. I want to talk briefly about it. So Copilot, for those who don't know about it, it's the AI extension for Spotfire that truly transforms how you interact with Spotfire. You can ask Copilot for a lot of different question types, from general data analysis questions to questions that are specific to the Spotfire functionality. You can interrogate data, create visuals, edit visuals, all through natural language interactions. You can explain visuals. You can explain pages in Spotfire, and you can even generate Python data functions using Spotfire Copilot for you. Spotfire Copilot is an extension that is built on LLMs, and it is agnostic by design, which means that you can use Copilot with your preferred LLMs, service provider. We see more and more customers adopting Spotfire Copilot and deploying deploying it to their users, and we've been able to observe how Copilot helps Spotfire users learn how to use Spotfire faster and helps experts move faster from questions to visualizations, explanations, and also code. We already have several webinars and recordings available, and dedicated entirely to Copilot. So if you want to deep dive into the topic, I definitely recommend watching these sessions. They give you a much deeper walkthrough and and live demos of Spotfire and and Spotfire Copilot. That said, I just wanted to provide, a quick update on what the Copilot team has been up to this year. First, we Spotfire Copilot two point o that was released 2025, expanding support to Spotfire web clients and consumer users, extending support for creating more charts, including tree maps, pie charts, waterfall charts, great improvements in the accuracy of the answers and the way it responds, with narrations of the analysis and also introducing a brand new user interface that is much more consistent, with the overall Spotfire experience. So that is for copilot2.o. And just a few days ago, a new update to Copilot with copilot two dot one, which improved with improved, visualization explanations, taking into account both the visualization itself and the underlying data to provide better accuracy in the in the response. And plus we are co pilot two dot one also improve connectivity, security, deployment, much much, streamlined deployment, as well as integrated observability by supporting, specific user action logs. So that's what I wanted to share about Spotfire. Now let's move to Spotfire. Remember, Spotfire bundles all the Spotfire and Statistica Server component into one product, Spotfire Server, automation services, statistics services, Spotfire, and Statistica Server. Spotfire adds new capabilities that simplify administration, enhance automation, and streamline enterprise deployments. And these improvements makes it easier for IT and administrators to scale Spotfire securely and efficiently across large, organizations. Since Spotfire, we have been having updates of the Spotfire, server components with every disease, always adding modern database support, being certified for latest enterprise databases, making evolving the platform for modern enterprise security, adding encryption, secure authentication support, everyone in the product. We have may we are making license management much simpler. We have make we have been making great improvements also, in scheduling jobs, monitoring jobs. We have have much more granularity when you schedule, schedule jobs, for instance, and you can be notified about their statue with, if, an operation fails or succeed, you can be notified via email or directly via an API that could, for instance, send it out to your preferred collaborations, for instance, in Teams. We have been adding APIs, APIs to manage the library, APIs to manage licenses, APIs to manage, migrations, of contents. And we are always also making sure to to stay current with the latest OS, updates. For administrations administration administrator, sorry, we are updating our web administration interface with every release, making sure it's, as easy as possible to use. In Spotfire 14 six, we are adding configuration of timeouts. Timeouts are now configurable at the job level in automation services, and it allows you to, it allows long running and short running job to have different execution or or wait time limits, while still maintaining a default for the average job. On the web administration UI side, we are adding support for we are making tables fully custom configurable. So you have, as I mean, much greater control on the sorting, or in the sizing of the tables, rearranging columns as well. You can choose what columns to display. You can export these these data tables. You can also save these tables as views so you can reuse them, very easily. We are also introducing in 14 six LTS new commands to make it faster and more reliable to migrate an existing existing Spotfire libraries to external storages such as Amazon AWS, Amazon s three, Azure Blob Storage, or Google Cloud Storages. And we think that these tools really simplify enterprise migrations, and providing you with a controlled workflow for managing a product environment to any support cloud providers. And as always, keeping our platform current, we are updating Spotfire to add support to the latest enterprise platforms into including Debian 30, supported as operating system, and Windows Server '20 25 also supported as operating system. So that's what I wanted to share with you today. I see time is passing, and I I just showed you a very small extract of everything new in Spotfire. If we get back to Spotfire 14 LTCS that was released about two years ago, Spotfire 14.6 LTCS is a combination of six releases, more than a 110 new features, 90 plus customers' IDs delivered. You have the full list here. I don't ask you to read them all, but I think we are delivering rate value with Spotfire 14.6 HES, and we are really looking to hear from you. JP, you want to say something? I do indeed. Thank you very much, everyone, and thank you very much, to you, Arnaud for that insightful presentation. Once again, thank you to everyone who joined us today. Now we did receive quite a few different questions through the q and a function of the platform. Just before we get onto that, just a few things that we wanted to share. If you wouldn't mind going over to the next slide, Arnold. In terms of our webinars, we have two great series all being added to on a regular basis. So whether you're looking to find out more about Spotfire or are looking to learn about the latest in terms of what's new, please don't hesitate to register to the full series. Our next webinar will actually be next week on the October 23 where we'll be diving into, a few different high-tech manufacturing use cases, and we will have Renesas, one of our customers, who will be presenting with us and showcasing, the successes they've had with Spotfire. Additionally, with regards to today's, on demand recording, a recording of today's webinar will be made available soon, so please do keep an eye on your inbox for the link. If you wouldn't mind shifting over to the next slide, Almo. Now in case you're interested in learning more, please do not hesitate to visit our website at spotfire.com or contact us directly. There are lots of ways to interact with us, whether it is via our socials, through our community. Additionally, our blog site has lots of great content where we share the latest on visual data science, dive into Spotify data science in more detail. And last but not least, if there are any additional enhancements that you would like to see or have any ideas that you would like to share with us, please don't hesitate to visit our ideas portal and log your great ideas. Once again, thank you very much for joining us today, and we hope to see you at our future webinars. Thank you once again, and have a great day.