BIG DATA MANAGEMENT

Dashbot Launches Conversational Data Cloud™ to Provide a Centralized View of All Chatbot Data

Dashbot | July 04, 2022 | Read time : 3 min

Dashbot
Dashbot, a conversational AI and data platform, today announced the launch of its proprietary Conversational Data Cloud™, letting customers build and optimize their chatbots from their businesses’ own conversational data. Dashbot’s Conversational Data Cloud™ turns unstructured, noisy, interrelated and often tangled conversational data into immediate action.

Across an ever-increasing number of communication channels (contact centers, support tickets, social media, IVR, live chat, etc), a business can get up to three million customer messages per day. The pandemic has significantly accelerated this flood of customer communications. In addition, the complexity of human language makes it impossible to predict every way users will speak with bots. As a result, over 50% of chatbot sessions fail. Optimizing existing bots can reduce failure rate by up to 35% and reduce escalation rate by up to 57%.

Dashbot’s Conversational Data CloudTM enables businesses to:
  • Centralize all conversational data including chatbot transcripts, Zendesk, email and live agent voice calls.
  • Decipher tens of thousands of daily conversations and transcripts.
  • Group similar messages and topics to determine areas of failure and opportunities for new use cases, leveraging its proprietary machine learning algorithms.

“We’re expanding beyond reporting and analytics to be able to ingest raw conversational data which can be difficult, but also very valuable for our customers,” said Andrew Hong, CEO of Dashbot. “We’re on a mission to decipher language, which is one of the most complex types of data that has ever existed. We listened to our customers that are challenged to make sense of all their conversational data, so we built our Conversational Data Cloud™ to help businesses automate, analyze and optimize their conversation channels.”

Dashbot’s Conversational Data Cloud™ is powered by three core features:
  • Transcript Transformer: Ability to search and categorize thousands of daily transcripts
  • DashbotML: State of the art machine learning models hypertuned from over 10 billion conversations. Topic Modeling to visualize flow and conversation loops. Phrase clustering (message grouping) to identify new use cases and unhandled topics.
  • Automated Training Data: Export messages as training data to optimize NLP model.

One Dashbot customer example is Intuit. With QuickBooks Assistant having so much unstructured data, they were spending days trying to manually identify mishandled or unhandled intents. In turn, their customers were getting annoyed with inaccurate responses and escalation to a live agent. They were able to leverage Dashbot’s Conversational Data CloudTM to benchmark the current state of their chatbots, and then identify and prioritize the highest impact tactics to improve.

About Dashbot
Dashbot is a conversational AI and data platform helping businesses to build and optimize their interactive voice response and chatbots. With Dashbot’s Conversational Data Cloud, the company is turning the most unstructured, noisy, interrelated and often tangled conversational data into immediate action. They are the only company to surface patterns with mishandled and unhandled intents to improve NLP engines, leveraging their proprietary Conversational Data Cloud™. Dashbot works with leading enterprises such as Intuit, Expedia, Geico, Google and Travelers, among many others.

Spotlight

In our connected world there's an increasing amount of "digital exhaust," data resulting from all kind of activities, that’s being created every moment. Take a look at how this data may impact us in future.


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BIG DATA MANAGEMENT

IBM Aims to Capture Growing Market Opportunity for Data Observability with Databand.ai Acquisition

IBM | July 07, 2022

IBM today announced it has acquired Databand.ai, a leading provider of data observability software that helps organizations fix issues with their data, including errors, pipeline failures and poor quality — before it impacts their bottom-line. Today's news further strengthens IBM's software portfolio across data, AI and automation to address the full spectrum of observability and helps businesses ensure that trustworthy data is being put into the right hands of the right users at the right time. Databand.ai is IBM's fifth acquisition in 2022 as the company continues to bolster its hybrid cloud and AI skills and capabilities. IBM has acquired more than 25 companies since Arvind Krishna became CEO in April 2020. As the volume of data continues to grow at an unprecedented pace, organizations are struggling to manage the health and quality of their data sets, which is necessary to make better business decisions and gain a competitive advantage. 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Databand.ai's open and extendable approach allows data engineering teams to easily integrate and gain observability into their data infrastructure. This acquisition will unlock more resources for Databand.ai to expand its observability capabilities for broader integrations across more of the open source and commercial solutions that power the modern data stack. Enterprises will also have full flexibility in how to run Databand.ai, whether as-a-Service (SaaS) or a self-hosted software subscription. The acquisition of Databand.ai builds on IBM's research and development investments as well as strategic acquisitions in AI and automation. By using Databand.ai with IBM Observability by Instana APM and IBM Watson Studio, IBM is well-positioned to address the full spectrum of observability across IT operations. For example, Databand.ai capabilities can alert data teams and engineers when the data they are using to fuel an analytics system is incomplete or missing. In common cases where data originates from an enterprise application, Instana can then help users quickly explain exactly where the missing data originated from and why an application service is failing. Together, Databand.ai and IBM Instana provide a more complete and explainable view of the entire application infrastructure and data platform system, which can help organizations prevent lost revenue and reputation. "Our clients are data-driven enterprises who rely on high-quality, trustworthy data to power their mission-critical processes. When they don't have access to the data they need in any given moment, their business can grind to a halt. "With the addition of Databand.ai, IBM offers the most comprehensive set of observability capabilities for IT across applications, data and machine learning, and is continuing to provide our clients and partners with the technology they need to deliver trustworthy data and AI at scale." Daniel Hernandez, General Manager for Data and AI, IBM Data observability solutions are also a key part of an organization's broader data strategy and architecture. The acquisition of Databand.ai further extends IBM's existing data fabric solution by helping ensure that the most accurate and trustworthy data is being put into the right hands at the right time – no matter where it resides. "You can't protect what you can't see, and when the data platform is ineffective, everyone is impacted –including customers," said Josh Benamram, Co-Founder and CEO, Databand.ai. "That's why global brands such as FanDuel, Agoda and Trax Retail already rely on Databand.ai to remove bad data surprises by detecting and resolving them before they create costly business impacts. Joining IBM will help us scale our software and significantly accelerate our ability to meet the evolving needs of enterprise clients." 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Alpha Serve Has Released Power BI Connector on ServiceNow Store

Alpha Serve | June 07, 2022

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VAST Data Accelerates CeGaT Genetic Data Analytics, Delivering Medical Insights Significantly Faster Than Competing Hybrid Storage Solution

VAST Data | July 29, 2022

VAST Data, the data platform company for the AI-powered world, today announced the company was selected by CeGaT to accelerate time-to-insight for genetic analytics essential to diagnostic healthcare, genetic research and pharmaceutical discovery. VAST’s high-capacity all-flash data platform replaces CeGaT's legacy hard-drive-based solutions, which constrained the company's genome sequencing application pipeline due to scale and performance limitations. Genome sequencing and genetic data analysis are crucial to discovering biomarkers that help doctors and scientists understand how specific diseases, such as cancer and diabetes, are formed. As genetics has evolved from the laboratory into diagnostic environments, these tools can now facilitate clinical decision-making to assist with advanced patient illness detection and make personalized medicine possible. Clinical genetics has enhanced patient care and is now an instrumental component of disease prevention and specialized targeted treatment. Since 2009, CeGaT has been helping doctors and patients find the genetic causes of rare diseases. Today, each of CeGaT’s genome sequencers generates up to five terabytes (TB) of data. This data must be collected, analyzed and interpreted quickly and accurately. When CeGaT recognized that its existing hybrid flash + HDD storage system couldn't keep up with growing demands for speed, volume and scalability, the company turned to VAST Data’s Universal Storage data platform. VAST’s Disaggregated and Shared Everything (DASE) architecture is a revolutionary leap in system scale, performance and resiliency. It brings the simplicity needed to support any scale of genomic data discovery, laying the foundation for the future of CeGaT’s ambitious growth strategy. Since deploying VAST, CeGaT’s ability to process genomic data through its pipeline has accelerated significantly, resulting in new compute hardware efficiency, savings and improvement to CeGaT’s overall business agility. “To support our scientific and healthcare agenda, we’re constantly pioneering new ways to extract new insights from larger and larger datasets. “When we began our search for new data infrastructure, we decided that our mission-critical business would not compromise on scale or uptime. VAST Data’s Universal Storage is an always-on platform that can easily scale with our data program. The system is fast, too. The improvement to our pipeline allows us to take on more work within the same infrastructure envelope, saving us money while also driving science forward and furthering data-intensive methods of scientific discovery.” Tim Scheurenbrand, IT director at CeGaT CeGaT can realize the vision of an all-flash data center, without incurring exorbitant all-flash storage costs. Universal Storage combines the high performance, low-latency and capacity of hyperscale all-flash storage with novel storage efficiency algorithms to make all-flash infrastructure affordable for ever-increasing datasets. “We chose VAST because the Universal Storage concept completely won us over,” added Scheurenbrand. “With VAST we get a highly performant all-flash system for the price of a less powerful hybrid storage system.” “CeGaT is committed to pushing the scientific boundaries of gene diagnostics, helping healthcare providers find the fastest path to patient therapy. With CeGaT, we are able to showcase the distinctive performance capabilities of our architecture and contribute to life-changing research. Ultimately, it’s about using technology for faster detection, prevention and personalized treatment plans, all in the pursuit of creating a healthier world. And that is a powerful reminder of why we do what we do,” said Peter Gadd, Vice President, International at VAST Data. About VAST Data VAST Data delivers the data platform at the heart of the AI-powered world, accelerating time-to-insight for workload-intensive applications. The performance, scalability, ease of use and cost efficiencies of VAST's software helps enterprise organizations overcome the historic barriers to building all-flash data centers. Launched in 2019, VAST is the fastest-selling data infrastructure startup in history.

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Factored Partners With dbt Labs to Strengthen Data Analytics Workflows and Generate Informative Insights

Factored | June 30, 2022

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