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The O’Reilly Data Show Podcast: Alan Nichol on building a suite of open source tools for chatbot developers. In this episode of the Data Show , I spoke with Alan Nichol , co-founder and CTO of Rasa , a startup that builds open source tools to help developers and product teams build conversational applications. About 18 months ago, there was tremendous excitement and hype surrounding chatbots, and while things have quieted lately, companies and developers continue to refine and define tools for b
All too often, software vendors view analytics as the end rather than the beginning of a process. I’m reminded of some of the advanced math classes I’ve taken in which the teaching process focused on a few key aspects of a mathematical proof or solution, leaving the rest of the exercise to be worked out by the students. In other contexts, you may hear people say the numbers speak for themselves.
When I was out for a walk recently, I heard a loud low-flying aircraft passing overhead. This was not unusual since we live in the flight path of planes landing at a major international airport about 10 miles from our home. In this case, I thought to myself that the sound seemed more directly overhead and lower than normal as well as being suggestive of a larger than average jet aircraft.
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
Looking to transform your data into a valuable, customer-facing data product? From concept to design and launch, we've worked with dozens of companies to create successful data products. Our checklist provides seven evaluation criteria to see if your data product has what it takes to succeed. Does your data product. Solve a distinct problem? Meet users where they work?
Today's manufacturing organizations operate in a dynamic environment characterized by increased complexity and uncertainty. The financial performance of manufacturers hinges on their ability to rapidly adapt to constantly-changing conditions, from demand fluctuations to delivery challenges while managing production costs efficiently. Prescriptive analytics helps companies see where process improvements could have the biggest, most immediate impact on their bottom line.
Getting DataOps right is crucial to your late-stage big data projects. At Strata 2017 , I premiered a new diagram to help teams understand why teams fail and when: Early on in projects, management and developers are responsible for the success of a project. As the project matures, the operations team is jointly responsible for the success. I've taught in situations where the operations team members complain that no one wants to do the operational side of things.
Getting DataOps right is crucial to your late-stage big data projects. At Strata 2017 , I premiered a new diagram to help teams understand why teams fail and when: Early on in projects, management and developers are responsible for the success of a project. As the project matures, the operations team is jointly responsible for the success. I've taught in situations where the operations team members complain that no one wants to do the operational side of things.
Retention marketing is about preventing your valuable customers from churning. Reducing customer churn requires you to know two things: 1) which customers are about to churn and 2) which remedies will keep them from churning. In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics.
Every company is a data company. Whether they know it or not. So argue Jedidiah Yueh and Randy Bean in this provocative look at the corporate landscape. The authors argue that data companies will reinvent the world.
We all know about the image classification problem. Given an image can you find out the class the image belongs to? We can solve any new image classification problem with ConvNets and Transfer Learning using pre-trained nets. ConvNet as fixed feature extractor. Take a ConvNet pretrained on ImageNet, remove the last fully-connected layer (this layer’s outputs are the 1000 class scores for a different task like ImageNet), then treat the rest of the ConvNet as a fixed feature extractor fo
This week, Gartner hosted its annual Security & Risk Management Summit in London and the buzz at the event centered on the new risks associated with the General Data Protection Regulation (GDPR). The discussion was fueled by the recent cyber attack experienced by British Airways (BA). BA disclosed the data breach just prior to our event and it was headline news in London throughout the week.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
Scott Hebner, VP, Marketing, IBM Analytics & AI, spoke with Dave Vellante in NYC on the eve of the September 13 taping of the Win with AI digital broadcast.
The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness. In this episode of the Data Show , I spoke with Sharad Goel , assistant professor at Stanford, and his student Sam Corbett-Davies. They recently wrote a survey paper, “A Critical Review of Fair Machine Learning,” where they carefully examined the standard statistical tools used to check for fairness in machine learning models.
The devastating impact of natural disasters can be measured in human suffering, loss of life and economic impact. It is estimated that 2.5 million people have been directly affected by natural disasters since 2000. Additionally, natural disasters have had an economic impact of $1.3 trillion since 2003. Even though natural events such as floods, earthquakes or hurricanes are inevitable, I believe that their impact can be mitigated through the application of data and analytics.
SQL development is not a new concept. However, as the data warehousing world shifts into a fast-paced, digital, and agile era, the demands to quickly generate reports and help guide data-driven decisions are constantly increasing. This puts new pressures on the people working behind the scenes to prepare and serve data in a consumable way to a growing audience with various levels of access credentials and technical expertise.
The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
The peterjamesthomas.com Data and Analytics Dictionary is an active document and I will continue to issue revised versions of it periodically. Here are 20 new definitions, including the first from other contributors (thanks Tenny!): Artificial Intelligence Platform. Data Asset. Data Audit. Data Classification. Data Consistency. Data Controls. Data Curation (contributor: Tenny Thomas Soman ).
A service provider or vendor might want to publish multiple copies of a report that should connect to different database servers or databases. In a true multitenant service solution, we would have a singe database with row-level user mapping tables that filter data by the logged in user.
If we’re going to think about the ethics of data and how it’s used, then we have to take into account how data flows. Data, even “big data,” doesn’t stay in the same place: it wants to move. There’s a long history of language about moving data: we have had dataflow architectures, there's a great blog on visualization titled FlowingData , and Amazon Web Services has a service for moving data by the (literal) truckload.
GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
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The worst thing about an inside job is that once it’s detected, it’s usually too late. Early detection is critical to prevent considerable damage arising out of insider threats to the business. But that’s easier said than done! Whether it’s a rogue trader in a bank or brokerage or someone illegally sharing company intellectual property or intelligence, illegal insider actions put enterprises at risk of losing millions.
By Jean S. Bozman. VMware is harmonizing the traditional management style of VMware software stacks with CSP cloud provider services – making it possible for VMware to help its customer base move more quickly to cloud-enabled environments. The VMware products that support this strategy were announced at VMworld 2018 in August, 2018. The aim of VMware’s strategy for hybrid cloud and multi-cloud deployments is to provide a consistent environment – whether it runs on-premises in a data center, or o
I’m managing an Agile team project using Microsoft Teams – the new project management platform integrated with Office 365. Teams is a simple and useful project management tool but it’s new and light on features. Using Power BI, we want to show the hourly task burn-down for each two-week sprint.
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Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
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