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Tag Archives: Source

ETL company Airbyte raises $5.2M to integrate open source data

March 3, 2021   Big Data
 ETL company Airbyte raises $5.2M to integrate open source data

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Airbyte today announced it has raised $ 5.2 million in seed funding as part of an effort to make open source tools for managing and integrating data more accessible.

The company, which offers an open source extract transform and load (ETL) tool used to create data pipelines, is now seeking to further democratize that process. This includes, for example, building complementary open source tools to govern and secure data, Airbyte cofounder and CEO Michel Tricot told VentureBeat.

Internal IT teams have historically employed ETL tools to move data between repositories. In recent years, however, data analysts have been using these tools to load data into warehouses without requiring any intervention on the part of an IT team.

All of those tools are licensed by individuals. Airbyte plans to eventually provide versions of its tools licensed by organizations, along with an option to access those tools via a service hosted by Airbyte. Tricot said the company is also planning a managed integration service. “We won’t be focusing on monetization until 2022,” he said.

Accel led the current round of funding, with participation from Y Combinator; 8VC; Segment cofounder Calvin French-Owen; former Cloudera GM Charles Zedlewski; Datavant cofounder and CEO Travis May; Machinify president Alain Rossmann; and Auren Hoffman, cofounder and CEO of LiveRamp and CEO of Safegraph.

As of the end of January, more than 600 organizations are using Airbyte ETL tools, including Safegraph, Dribbble, Mercato, GraniteRock, Agridigital, and Cart.com. Many of those organizations are attracted to Airbyte because they don’t have to wait for a provider of commercial ETL tools to create connectors for various data sources. Instead, the community collaboratively builds and supports the connectors it deems most critical, Tricot said. The community has thus far certified 50 connectors. Those connectors are encapsulated Docker containers, which enables them to be deployed on any platform.

ETL processes, along with other classes of data preparation tools, are being reevaluated as organizations increasingly realize that the quality of any AI model they build is dependent on how reliable the data used to train machine learning algorithms is. Data scientists also want to be able to easily update data needed to retrain models as business conditions evolve, which usually entails having more direct control over what data sources are employed to train those models.

As critical as control over any dataset may be, data scientists are discovering that much of the data stored within enterprise systems is not all that consistent or reliable. Data science teams can easily find themselves spending more time addressing data plumbing issues than they do constructing AI models. Successfully building an AI model, as a consequence, can often require months of time and effort.

ETL tools are not going to resolve that issue on their own. But the easier data becomes to manipulate, the less time it will take to build an AI model and then continuously maintain it as new data sources become available.

It’s not clear what impact the availability of open source ETL tools is having on providers of the rival commercial offerings some organizations have been employing for decades. But at a time when many organizations are under pressure to reduce the total cost of IT, the allure of open source software has proven undeniable.

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AI Weekly: The challenges of creating open source AI training datasets

February 20, 2021   Big Data
 AI Weekly: The challenges of creating open source AI training datasets

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In January, AI research lab OpenAI released Dall-E, a machine learning system capable of creating images to fit any text caption. Given a prompt, Dall-E generates photos for a range of concepts, including cats, logos, and glasses.

The results are impressive, but training Dall-E required building a large-scale dataset that OpenAI has so far opted not to make public. Work is ongoing on an open source implementation, but according to Connor Leahy, one of the data scientists behind the effort, development has stalled because of the challenges in compiling a corpus that respects both moral and legal norms.

“There’s plenty of not-legal-to-scrape data floating around that isn’t [fair use] on platforms like social media, Instagram first and foremost,” Leahy, who’s a member of the volunteer AI research effort EleutherAI, told VentureBeat. “You could scrape that easily at large scale, but that would be against the terms of service, violate people’s consent, and probably scoop up illegal data both due to copyright and other reasons.”

Indeed, creating AI training datasets in a privacy-preserving, ethical way remains a major blocker for researchers in the AI community, particularly those who specialize in computer vision. In January 2019, IBM released a corpus designed to mitigate bias in facial recognition algorithms that contained nearly a million photos of people from Flickr. But neither the photographers nor the subjects of the photos were notified by IBM that their work would be included. Separately, an earlier version of ImageNet, a dataset used to train AI systems around the world, was found to contain photos of naked children, porn actresses, college parties, and more — all scraped from the web without those individuals’ consent.

“There are real harms that have emerged from casual repurposing, open-sourcing, collecting, and scraping of biometric data,” said Liz O’Sullivan, cofounder and technology director at the Surveillance Technology Oversight Project, a nonprofit organization litigating and advocating for privacy. “[They] put people of color and those with disabilities at risk of mistaken identity and police violence.”

Techniques that rely on synthetic data to train models might lessen the need to create potentially problematic datasets in the first place. According to Leahy, while there’s usually a minimum dataset size needed to achieve good performance on a task, it’s possible to a degree to “trade compute for data” in machine learning. In other words, simulation and synthetic data, like AI-generated photos of people, could take the place of real-world photos from the web.

“You can’t trade infinite compute for infinite data, but compute is more fungible than data,” Leahy said. “I do expect for niche tasks where data collection is really hard, or where compute is super plentiful, simulation to play an important role.”

O’Sullivan is more skeptical that synthetic data will generalize well from lab conditions to the real world, pointing to existing research on the topic. In a study last January, researchers at Arizona State University showed that when an AI system trained on a dataset of images of engineering professors was tasked with creating faces, 93% were male and 99% white. The system appeared to have amplified the dataset’s existing biases — 80% of the professors were male and 76% were white.

On the other hand, startups like Hazy and Mostly AI say that they’ve developed methods for controlling the biases of data in ways that actually reduce harm. A recent study published by a group of Ph.D. candidates at Stanford claims the same — the coauthors say their technique allows them to weight certain features as more important in order to generate a diverse set of images for computer vision training.

Ultimately, even where synthetic data might come into play, O’Sullivan cautions that any open source dataset could put people in that set at greater risk. Piecing together and publishing a training dataset is a process that must be undertaken thoughtfully, she says — or not at all, where doing so might result in harm.

“There are significant worries about how this technology impacts democracy and our society at large,” O’Sullivan said.

For AI coverage, send news tips to Khari Johnson and Kyle Wiggers and AI editor Seth Colaner — and be sure to subscribe to the AI Weekly newsletter and bookmark our AI channel, The Machine.

Thanks for reading,

Kyle Wiggers

AI Staff Writer

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How the pandemic is accelerating enterprise open source adoption

January 27, 2021   Big Data
 How the pandemic is accelerating enterprise open source adoption

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Enterprises increasingly shifted to open source software solutions in 2020 to meet their remote organizational needs and address new market demands for quality and speed. COVID-19 challenged not only the economy, but also enterprises’ existing frameworks for how, when, and at what volume people use information technology.

Last year, major players like LinkedIn and Spotify open-sourced tools they developed — from Java machine learning libraries to audio file processing ecosystems — for non-proprietary IT team members like data scientists and software engineers to use. Seed-level startups like Eradani and RudderStack that built their products on open source thrived despite launching only a few months before the pandemic began to escalate.

Most companies don’t publicize their internal tooling and infrastructure strategy transformations, but GitHub’s data suggests these have much to do with open source solutions. GitHub says 72% of Fortune 50 companies used GitHub Enterprise, which runs GitHub services on their local networks, between Q4 2019 and Q3 2020. GitHub also found over 40% YOY growth in open source project creation per any active user between late April 2019 and late April 2020. This first spiked with the pandemic in early March, when countries began to close schools, ban visitors, and initiate lockdowns en masse.

In an interview with VentureBeat, GitHub VP Mario Rodriguez said, “Open source project creation just kind of shoots up” after March. He added, “2020 is interesting because everything from a technology perspective got accelerated, and you were trying to do more and more.”

According to Rodriguez, “2020 also opened up a new set of talent from a software development perspective.”

Companies were previously limited by their geography and could only hire within certain cities, like San Francisco or New York. But the transition to remote work has begun to change that.

“Now, you do not have those restrictions … and the majority of software developers out there use open source today. And so you bring it into your enterprise now at an accelerated rate, which allows you to learn and continue to evolve your practices on how you develop software and how you use open source,” he said.

The pandemic disrupted existing tech trends and likely helped amplify the growing movement toward open source software solutions as enterprises’ distributed, remote workforces needed to use more custom applications internally, to innovate their IT quickly with the help of reusable code, and to retain developers by using the tools they prefer.

Speed: Accelerating technology with a remote, distributed workforce

Internet traffic skyrocketed by over 30% in March, especially to platforms for online learning and telecommuting. Microsoft Teams users set a new record for 2.7 billion meeting minutes in one day, and Microsoft, along with Netflix and YouTube, temporarily reduced video streaming quality and download speeds to cut back on bandwidth consumption.

These changes highlighted consumer demands for new digital communication tools and challenged enterprise IT teams to create and manage them — quickly. And enterprise IT teams, now distributed and in some cases fully remote, had to organize their own work around new kinds of applications and develop them in days or weeks, as opposed to months or years.

“From an IT perspective, you have to accelerate the [number] of apps that you are creating for your internal use as an enterprise,” Rodriguez said. “So that has actually allowed the enterprises to say, ‘You know what, if we are going to have these constraints, maybe we should start to research and figure out a way to empower more use of open source internally, as well.’ … You’re trying to go faster.”

While some enterprise frameworks and custom logic for business applications remain fully proprietary, integrating open source code can be a faster way to develop most software. Developers can import the existing work of thousands of people with a few inputs, making it easier to pull new applications together. For example, companies expedite their training and development of machine learning models with Google’s TensorFlow. Now that information is more democratized with open source software, some enterprise leaders suggest it’s hard to compete without it.

“I’m a member of the CTO forum, which is a group of 150 CTOs around the globe that talks a lot about tech,” Pinterest head of engineering Jeremy King said in a recent interview with VentureBeat. “And for sure, lifecycles have sped up.”

King described how companies used to try out maybe three or four vendors with an open source technology stack at a time for six months. Afterward, the company might figure out which vendor performed best and negotiate a rate.

“All that has gone away,” King said. He said if a company knows that a given open technology works, they’ll make a prototype and they’ll have changed the cycle by the next week.

“People are more rapidly adopting [open source], and I think it’s just because the tolerance for failure and making mistakes and moving quick has gone up,” he said. He explained that this is also true when it comes to “dealing with the consequences of moving fast in production, which, a year ago was unheard of.”

Elephant Ventures CEO Arthur Shectman also commented on the pandemic’s disruption of enterprise IT in an interview with VentureBeat. “The market kind of collapsed around people. In that moment of high volatility or prices and market stress, you reach for data,” Shectman said. “You’re like, ‘These decisions are going to have profound impacts … the net impact a week from now is huge.’”

Elephant Ventures is a digital transformation consultancy that helps corporations like Pfizer and American Express build their engineering capabilities. Shectman said he applies a technology readiness framework to his approach, finding ways for clients to create increments of business value with ETL technologies, API tooling patterns, and other strategies for deploying applications and workflows.

According to Shectman, “People were clamoring for data, and they were clamoring to transform their kind of data ecosystems, very rapidly.” He said that in the past few months, the conversation went from planning out three years of digital transformation retool to looking for immediate answers with a return on investment in 90 days. Shectman noted that waiting to purchase proprietary software could cost his enterprise clients $ 3 million in some instances.

Shectman said proprietary software’s cost and speed of deployment became greater roadblocks for his clients during 2020. “I felt like there was a lot more willingness to instantly adopt open source technologies and start applying them without any additional kind of software purchase cost to get a rapid ROI cycle project,” Shectman added. “Over the last year, if you could demonstrate that you knew how to implement it, you had a pattern that generated success in critical dimensions.”

Volume: Innovating with code reuse and existing tools

Developers can build applications at greater volumes by reusing open source code instead of starting from scratch. Enterprise IT teams can also integrate open source tools into their existing workflows to manage their data with improved precision. This control is increasingly important, given the pandemic’s overall shift toward digitalization, which increases the amount of data itself.

“The number of apps that get created right now are at an all-time high. And then the number of those apps that [use] open source are also at an all-time high. It’s probably because of code reuse and ability to just go from zero to 60% or 70% of what you need to create very, very quickly,” Rodriguez said.

These current trends in open source software are a continuation of many enterprises’ strategies. “I think we use a lot of open source technologies, largely due to the fact that our scale often prevents us from using a commercial product,” King said.

“Pinterest is a 10-year-old company, and we have billions of pins … and that’s not always something you can just buy off the shelf. And so whether it’s logging data, understanding images, searching — all these technologies didn’t exist when we started; they’re getting better and better over time. Even the off-the-shelf cloud providers are getting better. But we’ve made Pinterest very unique to what we’re looking for as a result of us using a lot of open source technology,” he added.

Other enterprises have tailored their tech stacks to maximize productivity and output with open source solutions more recently. Even maintaining the same products requires additional speed of deployment when competing in a volatile COVID-19 era market.

McKinsey reports that North American businesses accelerated their share of digitized product offerings by 20% between March and October 2020. Open source software might play a role in expediting this process if the bulk of digitized products’ code can be built from an existing repository’s code.

“For a long time, the digital economy and the computer revolution were just driven by Moore’s law, with your chips getting better and faster at this crazy growth rate,” Shectman said as he traced his client’s technology solutions from the early 2000s to late 2020. “Now, after you go through the early iterations of your product, you are able to do a certain amount of things with commercially available software, [but] you’re gonna have typically an easier time unwrapping and fixing or customizing the open source stuff.”

According to Shectman, understanding and acting upon data has become key to enterprises. “I think it’s the scale of data production. I don’t think anybody really had a great sense of how rapidly data would proliferate in the world.”

The market’s space for tools, particularly open source technologies that sieve and curate data, has widened as a result. In the past 30 years — and mostly in the last 10 — over 200 companies with open source technology at their core have raised over $ 10 billion in capital.

Startups such as data warehousing platform RudderStack, which provides an open source-based alternative to Segment, have recently capitalized on this change. RudderStack was launched in late 2019, and its 2020 growth mirrors the growth patterns of other early-stage startups, like Prisma and Streamlit, which contribute to GitHub community code and base their business strategies in open source software.

RudderStack marketing lead Gavin Johnson said in an interview with VentureBeat, “Being open source makes it easy to deploy RudderStack in your own environment. … Anyone can look through the code and figure out what is being done with their customer data in-product, something you can’t do with closed-source products.” According to Johnson, RudderStack’s open source software reduces the number of tools enterprise engineering teams would have to build for sending and collecting data and allows the teams to modify the platform with custom integrations. He also suggested end-user enterprise IT teams tend to save more money with these alternatives to proprietary platforms.

Novelty: Energizing IT teams and long-term growth

The Linux Foundation reports that in 2020, 93% of hiring managers found it difficult to recruit employees with open source software skills and 37% of them wanted to hire more skilled IT professionals, despite the pandemic’s economic impact.

Rodriguez told VentureBeat that in 2020, “We didn’t see companies shrink in developers. We actually saw them expand in developers.” He believes this growth has to do with enterprises’ goals that now, more than ever, revolve around IT capabilities.

“You’re trying to create all this software, which means that you need more developers in order to do it right. And if you’re trying to actually have more, [you need] to not only have the best tools for your developers but have the best practices as well.” He said that is another reason he thinks open source accelerated significantly in 2020.

The open source community organizes conferences, groups, and companies around making code more accessible. Developers contribute to repositories like Open Source for Good and develop personal projects with open source code.

Johnson said that data engineers and data scientists work a lot in open source. He said, “RudderStack’s mission is to help make engineering and data teams be heroes of their organizations. So we needed to build our product in a way they like, which means open source.”

Some enterprises are turning to open source tools to bring in skilled technical employees. King said open source attracts and retains engineers. “And the people who are the best in the world want to publish, and they want to work on things that are well known, and they want to contribute back. And so it is definitely a good return on investment as well,” he said.

In addition to using open source for internal transformations, enterprises have been contributing open source tools to the community. Open source contributions can improve enterprises’ visibility and relevance, and this business strategy is important now that most, if not all, of their public operations are digital. RedHat brings open source technologies to enterprises that need them and has since it was founded in 1993. But in 2020, end-user companies like Facebook, LinkedIn, Spotify, and Uber have also begun to open-source their own tools for the public.

“The open source movement is pretty well established and reasonably mature at this point, so it’s not a surprise for any large corporation,” Shectman said. “If there’s a bit of awareness, people can afford to shy away from some of the convenience of a particular vendor-specific thing in order to allow themselves fluidity.” Shectman suggested that businesses face similar constraints with their staffing, technology, and ability to create effective products. He added that he’s seen open source software help businesses remove constraints, including proprietary vendor lock-in.

Rodriguez suggested that the advancements open source can provide in regard to speed, volume, and overall business strategy aren’t easily matched. “What everyone now is realizing is you cannot out-innovate, or you cannot out-execute open source,” he said.

Will open source continue to grow in 2021 like it did in 2020? Rodriguez thinks it could. “For any company out there, from the most powerful company in the world to a startup, you’re not going to be able to hire [enough] people to build the software of that quality — open source gives you that immediately.”

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#PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

December 29, 2020   Self-Service BI

I have been playing around with the new awesome (preview) feature in the December Power BI Desktop release where we can use DirectQuery for Power BI datasets and Azure Analysis services (link to blogpost)

In my case I combined data from a Power BI dataset, Azure Analysis Services, and a local Excel sheet. The DirectQuery sources was in a test environment.

I then wanted to try this on the actual production datasets and wanted to change the datasources – and was a bit lost on how to do that but luckily found a way that I want to share with you.

Change the source

First you click on Data source settings under Transform data

 #PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

This will open the dialog for Data source settings and show you the list of Data sources in the current file.

 #PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

Now you can either right click the data source you want to change

 #PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

Or click the button “Change Source…”

 #PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

Depending on your data source different dialogs will appear

This one for my Azure Analysis Services Connection

 #PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

And this one for Power BI Dataset

 #PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

And this one for the Local Excel workbook

 #PowerBI – Change the data source in your composite model with direct query to AS/ Power BI Dataset

Hope this can help you to.

Happy new year to you all.

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Erik Svensen – Blog about Power BI, Power Apps, Power Query

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Microsoft Teams Calling Provides Additional Support for a Single Source for all CRM Information

December 9, 2020   Microsoft Dynamics CRM

The remote workforce is growing. This includes organizations’ sales and marketing teams, which used to relied on face-to-face interactions both in the office and in the field. To maximize the productivity of their sales and marketing teams, organizations now provide them with support in the form of centralized CRM solutions that provide full visibility into their customers and prospects, and all the tools to connect with them effectively.

The integration of Microsoft Dynamics 365 Customer Engagement apps including Dynamics 365 Sales with Microsoft Teams provide sales and marketing with the all the information and communication channels they need to feel empowered to do their job exceptionally. Microsoft Office 365 transforms the workplace with Microsoft Teams that unifies communications of all types, including calling, from one central location. 

Note: Microsoft Teams integration uses SharePoint integration at the backend. Some prerequisites may be required for the full integrated Customer Engagement experience. More information on how to get assistance can be found at the end of this article.

x2020 12 07 13 25 45 625x350.jpeg.pagespeed.ic. Quu8qhybl Microsoft Teams Calling Provides Additional Support for a Single Source for all CRM Information

Microsoft Teams serves as a centralized virtual workspace and intranet hub for communication, collaboration, connectivity, and more.  Microsoft Teams allows users to call, chat, meet and collaborate virtually in one app, with all the internal, customer and prospect information they need within reach. Making calls in Teams is easy to learn and quick to adopt. It also offers extensive device support to enable calls to be made from anywhere. 

Here are just 3 of the top benefits Microsoft Teams calling provides to CRM processes 

1. Rich personal calling features

Instead of using multiple systems to look up phone numbers, dial the number, and track the history of conversations, Microsoft Teams brings all the calling capabilities to one place. Through an easy-to-navigate UI in Microsoft Teams, users have everything they need to easily make and receive calls, as well as manage their call settings, queues, devices, contacts, auto attendant, delegation, voicemail, history and reverse number lookup.  

2. Collaborative Calling and Delegation Support

Busy sales and marketing teams may need additional assistance in the form of screening calls so that they can prioritize their efforts. Teams offers collaborative calling features for any user responsible for fielding calls at the organization. A shared voicemail queue allows authorized users to listen and process voicemails. 

An especially helpful collaborative calling feature is Delegation. Users can assign their delegates based off a list of existing delegates as well as choose and add new delegates. Delegation allows users that have been assigned as a delegate to manage their delegator’s calls and access contacts, call history and voicemail. Calls can transfer to delegates first, who can put the caller on hold, transfer to the intended recipient live, or to voicemail. 

3. Multiple device support and Microsoft-certified devices 

Microsoft Teams maximizes efficiency with calling capabilities supported on multiple devices. This includes transferring calls between desktop and mobile, or adding devices. In addition to support for most devices, Microsoft has a certified portfolio of Teams devices optimized for the highest quality Teams and calling experience. This includes peripherals and room systems (e.g., headsets, speakerphones, Teams Rooms technology, webcams, etc.), desk phones and displays. 

Other benefits…

In addition to the benefits above that are more user-focused, Microsoft Teams calling also benefits IT and the organization at-large. Microsoft Teams calling streamlines management for IT through central management of user provisioning, phone number assignment, and porting existing numbers right from the Microsoft 365 Admin Console. To enable Microsoft Teams calling, organizations are offered flexible choices including cloud-based Microsoft Calling Plans, or can stay with their existing (or choose a new) telecom provider and connect via direct routing. Organizations also have the option to do both!

Whatever your choice, JourneyTEAM wants you to get the most out of your organization’s intranet system and is here to help.

Click here to see the full article

JourneyTEAM was recently awarded Microsoft US Partner of the Year for Dynamics 365 Customer Engagement (Media & Communications) and the Microsoft Eagle Crystal trophy as a top 5 partner for Dynamics 365 Business Central software implementations. Our team has a proven track record with successful Microsoft technology implementations. Consolidating your communication, collaboration, and productivity platform with Microsoft will provide the best support possible for your sales, marketing, and other teams, wherever they work. Let us show you how. Contact JourneyTEAM today!


177x247x2020 08 24 15 32 44.jpeg.pagespeed.ic.GxqNPDY2JL Microsoft Teams Calling Provides Additional Support for a Single Source for all CRM InformationArticle by: Dave Bollard – Chief Marketing Officer  | 801-436-6636

JourneyTEAM is an award-winning consulting firm with proven technology and measurable results. They take Microsoft products; Dynamics 365, SharePoint intranet, Office 365, Azure, CRM, GP, NAV, SL, AX, and modify them to work for you. The team has expert level, Microsoft Gold certified consultants that dive deep into the dynamics of your organization and solve complex issues. They have solutions for sales, marketing, productivity, collaboration, analytics, accounting, security and more. www.journeyteam.com

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Join us for Open Source Community Day October 15

August 23, 2020   TIBCO Spotfire
TIBCO OpenSourceCommunityDay 696x464 Join us for Open Source Community Day October 15

Reading Time: < 1 minute

Open Source Community Day (#OSSDay) is back! 

Back in April, our TIBCO LABS team hosted our first #OSSDay; a free virtual one-day conference for developers and other technical professionals, that focused on the latest technologies in open-source.

Missed our last #OSSDay? Watch all of the sessions on-demand. 

Due to the popularity of the event, we are happy to be hosting Open Source Community Day (Fall Edition) #OSSDay, October 15th. Similar to the last event, this one will also be FREE! This event is geared for anyone interested in learning more about open source technologies.

We are happy to be hosting Open Source Community Day (Fall Edition) #OSSDay, October 15th. Similar to the last event, this one will also be FREE! Click To Tweet

The day-long interactive event featured topics such as:

  • AWS: 2020 ML Ops State of the Art
  • GitLab: Automating Kubernetes Deployments
  • Project Air: How to Collect, Process, and Visualize IoT Data the Right Way
  • And more.

We have a great lineup planned, with speakers and industry leaders from TIBCO, AWS, Microsoft, Google Cloud, VMware, and Women Who Code Silicon Valley. Stay tuned for more details as the agenda unfolds.

The adoption of open source technologies is continuing to grow rapidly, so join us on October 15 for #OSSDay to learn more about the latest trends in various open-source projects. Register today.

TIBCO LABS is dedicated to helping TIBCO customers adopt emerging technologies to solve their toughest business problems. The team has created various projects that implement technologies such as AI/ML, AR, blockchain, cloud, IoT, process mining, and natural language processing, all of which are open source.

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TamilGun; Choose the Best Entertaining Source that Comes Free, But Offers the Best Stuff

April 8, 2020   Humor
Tamilgun 696x483 TamilGun; Choose the Best Entertaining Source that Comes Free, But Offers the Best Stuff

If you have been watching movies online for a long while, you must be familiar with the best entertaining site; the TamilGun or Tamil Gun providing pirated stuff to its users. That’s why it is going to be the ultimate option for all of your family to spend time when you are on the Internet. We undoubtedly love movies and want them even more if we get them for free.

This is known as the most significant website that’s been online for over many years and serving thousands of free downloadable movie links to its fans. You can watch the latest movies, new TV shows, eye-opening documentaries, and a lot more. Here you may get links to HD movies in various genres, like romance, horror, crime, comedy, action, adventure, and thriller, etc. 

If you are seeking a way to download the film you want to watch in your spare time. You won’t be disappointed with this entertaining web portal. There is a variety of Tamil, Telugu, Malayalam, Bollywood, and Hindi dubbed; versions of the movies from various other regions, and countries.

Enjoy The Marvelous Experience Of Watching Movies At Home

Watching all of your favorite shows, programs, and latest movies have turned into a great experience. Since the dawn of various online streaming services like Amazon, HBO, Hulu, and Netflix, etc. But there is a flaw with these sites that they offer entertainment against a big monthly fee.

Here is a question worth a million dollars. What if you don’t want to pay any of your money on watching the latest movies on these paid sites?

What if you don’t want to go to the theater on the upcoming Saturday night; and want to stay at home?

Here, in this critical situation, comes TamilGun as your ultimate choice to get free entertainment with your family. While sitting on your couch at home.

Some Quality Features and Amenities Possessed by Tamil Gun

One of the best offers made by Tamil Gun is to provide its users with the application for their Android, and iPhone smartphones. It has now become very convenient for movie lovers to watch their favorite movies on their smartphones. All you need is to have a smartphone with a reasonable RAM and ROM. Now get the app from the web, and start watching or downloading the movie. You are hereby suggested to get rid of all the cache, and unnecessary apps to lighten your smartphone.

No Registration, No Monthly Fee

You will appreciate the site for many reasons, and one of the most appreciated things about this fantastic entertaining web portal is that they offer everything free, and you don’t have to create an account to watch a movie. Instead, you are welcome to visit the site and instantly click on the movie, or your favorite series to start watching. Creating an account means to remember the details of the account and stress to keep them secret, yet this fantastic site is a friendly and entertaining platform.

What Is The Quality Of Data Presented On TamilGun?

You will be offered with two types of data on the site. In type 1 the content you may find is pirated, and it has poor quality. In this category, most of the movies are filmed in theaters with some Handycam or mobile cameras. Though the camera result never collects quality results, it breaks a majority of cinema viewers. Most of the viewers don’t come to the cinema and log on to the Tamil Gun and enjoy the latest movies at home.

This is why sites like TamilGun cause massive losses for filmmakers who have spent their money, effort and time to create the films. In the second type of content portion, there are high quality or Blu-ray results. These are rather old movies and are not shown in the theaters anymore. 

The Way Of Entertaining And Threatening Of TamilGun To Its Audience

This entertaining site offers its users with pirated and illegal entertaining stuff. And the biggest allure of the site, of course, is to present everything for “free”. It is typically a risky offer for tending to come with add-ons that might ruin your idea to watch the movies for free. Moreover, it is most probably going to rack up the cost as you might have to purchase to enjoy their offer.

On their site, you might also be prompted to get access to their several other programs that might not fall in the “free”. Truly speaking, it sounds very much like a trap or scam they spread there to rip off the users by depriving them of their money. If you can’t help watching movies there TamilGun, you are advised to secure yourself. This is also one of the sites, where the users are at high risk of losing their money, or privacy.

There are always sharp people behind all such sites. And they know how to get more against providing the free stuff. There is certainly the risk to infect your computer or smartphone, with a virus or malware. Therefore you must have the best anti-virus software to tackle this critical issue. Use some ad, and pop up blocker, and always use a reliable VPN, before going on such sites.

What is the Legality Status of Tamil Gun?

This is undoubtedly one of the best entertaining portals, which is delivering free stuff, yet it’s not entirely legal. They are not getting all the contents in a lawful manner. That’s why they have been banned many times, but they appear again with a new name. You are therefore recommended to avoid using such platforms to watch movies. Instead, you should spend some money on a monthly basis. And watch your favorite movies on legal sites like Amazon, Netflix, and Hulu, etc.

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Why a Single Source of Truth Often Isn’t

November 22, 2019   CRM News and Info

This week, Salesforce used its annual Dreamforce mega-show to make a host of announcements, ranging from contact center partnership with Amazon to a smart speaker tool for sales.

For the most part, the keynote featured practical applications of Salesforce technology. Some Dreamforces focus on the highly aspirational; others focus on the ways to attain those aspirations. This year is the latter.

However, Salesforce did get very aspirational with the announcement of Customer 360 Truth. Last year’s event followed the Mulesoft acquisition, and
the big idea was the unification of data across various cloud-based systems in something it called “Customer 360.”

The cloud has enabled companies to become profligate in their use of on-demand, easy-to-deploy applications, which started to silo and separate information — the exact issue that CRM was introduced to combat way back when companies lacked a single source of sales data.

This year Salesforce took that idea a step further. Customer 360 Truth aims not simply to aggregate that data but to organize it across sales, marketing, service, commerce and more. The goal is to create a complete view that reflects the reality of the customer at this moment, enabling the company to deliver a trusted, personalized, customized relationship with each customer.

The Fourth Wave

Applying technology to customer data for a more accurate understanding is not a new concept. More than a decade ago, InsideView began gathering information about customers, examining it, and presenting the pieces of data that were the most current. Even back then, the term “single source of truth,” or SSoT, was bandied about with enthusiasm.

Mark Benioff took that enthusiasm to the next level Tuesday by declaring that SSoT was the “Fourth Wave of computing.” That is dramatically overstating things. We’ve spent the last 35 years using technology to collect, collate and employ data about our customers. Data was scarce 35 years ago. Now we can collect a lot of it — and sure enough, it needs to be sorted. However, the fundamentals have not changed.

What I worry about is the term “single source of the truth,” and what it implies. In the context of a business, it means the most accurate data set in its possession. That is never going to be the sole source of truth about someone, or even the best source of truth. It just happens to be the source of truth your analytic systems have decided on, based on what your data collection systems have gathered. It’s useful — but be careful.

Getting to Know You – or Not

Every day, I am exposed to evidence that the “truth” about me, as understood by the data systems of various companies, bears very little resemblance to the actual truth (no quotes) about me. I regularly receive “targeted” ads on social media that are wildly off the mark: emails touting products similar to one-off purchases of gifts, or Halloween costumes bought for my daughter years ago, or direct mail asking for my support for causes that I’m diametrically opposed to.

These ads would suggest that I’m a Republican gun owner who wears lots of T-shirts and is really into Tinker Bell. That’s about as wrong as you can get it, and businesses waste lots of money on me believing it’s a real truth.

I’m sophisticated enough to know why these false indications exist: flaws in data collection, half-baked inferences about customers, sloppy data entry, and so on. This is where the concept of a SSoT can become derailed. No matter how much you invest in technology to pull data together, when you use faulty data to determine what is true, what you think is the truth will be faulty.

The other mistake businesses make is to believe they own the SSoT about customers. In reality, we each own the best SSoT about ourselves. However, data about people is much easier to manage and deal with than data from the people themselves. So businesses spend ever more money making educated guesses about their customers, doing increasingly complex digital detective work, and kidding themselves that their SSoT is a perfect reflection of reality.

Separating specious data from accurate data is important, but unless your processes ruthlessly eradicate spotty or off-base data collection, routinely challenge inferences and assumptions about what data means, and check in with customers to see if their truth is close to your truth, your single source of the truth could be your single biggest weakness.
end enn Why a Single Source of Truth Often Isnt

The opinions expressed in this article are those of the author and do not necessarily reflect the views of ECT News Network.


Chris%20Bucholtz Why a Single Source of Truth Often Isnt
Chris Bucholtz has been an ECT News Network columnist since 2009. His focus is on CRM and other topics surrounding buyer-seller relationships. He is director of content marketing for
NewVoiceMedia, and a speaker, writer and consultant. He also has written four books on World War II aviation.
Email Chris.

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Multiple data source definitions on the On-premises data gateway for the same data source

July 6, 2019   Self-Service BI

Gateway management until recently, supported only one data source definition per data source on an on-premises data gateway. This posed limitations for gateway admins as they couldn’t create multiple data sources to the same data source each with different credentials based on the required security context for each one. The workaround would be to spin up a new gateway for every such new data source.

Note: The data source name still needs to be unique for every data source definition.

Below you can see that a gateway admin has created two data source definitions for the same database AdventureWorks2017 on the same server.

Once you publish a Power BI report, in the Datasets settings, you will be able to see the list of data sources you have access to as below. You can now select one of these data sources.

If you are a gateway admin, you could also additionally choose to add a new data source(as shown below) and that would take you to the Manage Gateways page to create a new data source.

If you have access to only one data source, you must explicitly select that data source.

Once all required data sources have been set up and selected, click on apply to bind this dataset to the selected data source on the gateway.

Note: This feature is currently available only for datasets. We plan to release the same feature for dataflows soon. Currently in dataflows, until this change is rolled out, the first available data source would be automatically selected.

Do try out this feature and provide your feedback. As always we would love to hear from you, learn from your experience and improve based on your feedback.

Thank you!

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Tier IV raises over $100 million to develop open source software for driverless cars

July 6, 2019   Big Data
 Tier IV raises over $100 million to develop open source software for driverless cars

Tier IV, a Japan-based driverless car software maintainer and provider, this week announced the closure of a round north of $ 100 million led by Sompo Japan Nipponkoa Insurance, with participation from Yamaha Motor, KDDI, JAFCO, and Aisan Technology. The fresh capital brings the company’s total raised to nearly $ 130 million following seed rounds totaling $ 28 million, and founder Shinpei Kato said it’ll fuel the global commercialization and expansion of Tier IV’s self-driving technology platform.

“Tier IV has a mission to embody disruptive creation and creative disruption with self-driving technology. We have derived a solid software platform and successfully integrated it with real vehicles,” said Kato. “It is time to step forward to real services, embracing functional safety and risk management.”

Tier IV, a University of Tokyo spinout founded in December 2015, spearheads the development of Autoware, which it describes as an “all-in-one” open source and BSD-licensed solution for autonomous vehicles. The platform supports things like 3D localization and mapping, 3D path planning, object and traffic signal detection, and lane recognition, plus tasks like sensor calibration and software simulation.

Tier IV funds this development in part by selling support equipment like remote controllers and logging devices, as well as desktops and laptops with Autoware preinstalled. Additionally, it offers subscription access to its data sets, labeling tools, and deep learning training services for $ 1,000 per year.

Tier IV’s stated mission is to “democratize” intelligent cars by enabling “any individual or organization” to contribute to their development. To this end, it and partner companies Apex.AI and Linaro 96Boards launched the nonprofit Autoware Foundation last December, which seeks to deploy Autoware in production products and services. The Foundation counts 30 companies among its membership, and Tier IV claims that Autoware has already been adopted by more than 200 organizations around the world to date, including Udacity (for its Nanodegree Program), the U.S. Department of Transportation Federal Highway Administration (in its CARMA platform), automotive manufacturers, and “many” self-driving startups.

Field tests of Autoware-powered cars have been conducted in over 60 regions in Japan and overseas “without incident,” according to Tier IV, and the company claims that vehicles running on its platform achieved level 4 autonomy (meaning they could operate safely without oversight in select conditions) as early as December 2017.

Tier IV competes to an extent with Baidu, which offers an open source driverless software stack of its own in Apollo. The Beijing-based tech giant claims that Apollo — which has grown to 400,000 lines of code, more than double the 165,000 lines of code the company announced in January 2018 — is now being tested, contributed to, or deployed by Intel, Nvidia, NXP, and over 156 global partners, including 60 auto brands. Notable Apollo collaborators include Chinese automobile manufacturers Chery, BYD Auto, and Great Wall, Hyundai Kia, Ford, and VM Motori.

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