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Category: Computing & data (Page 1 of 41)

Topics include computing platforms, analytics, data modeling and databases, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing, and machine translation.

DataStax unveils Astra Streaming

DataStax announced Astra Streaming, a scalable, multi-cloud messaging and event streaming platform built on Apache Pulsar. Astra Streaming is integrated with DataStax’s marquee serverless database, Astra DB, to deliver a multi-cloud solution for managing both data in motion and data at rest. With the introduction of Astra Streaming, DataStax aims to deliver on its vision of an open data stack for today’s multi-cloud applications that require massive scale, zero-downtime availability, and high performance. Astra Streaming Features:

  • Global scale, cloud-native streaming, powered by Apache Pulsar without the complexity of self-managed solutions
  • Compatible with Apache Kafka and Java Messaging Service
  • Multi-cloud
  • Simple developer APIs for streaming
  • Handles high-volume queuing and pub-sub messaging and more complex messaging patterns
  • Pay-as-you-go pricing

Astra Streaming is available today in a beta version. To get started with Astra Streaming, create a free account.

DataRobot releases DataRobot 7.1

In its second major release of the year, DataRobot announced several product upgrades to its Augmented Intelligence platform designed to further democratize AI. The 7.1 release introduces:

  • MLOps Management Agents – DataRobot’s MLOps Management Agents provide advanced lifecycle management for an organization’s remote models. Management Agents understand the state of any remote model regardless of how they were created or where they are running, and can automate various tasks.
  • Feature Discovery Push-Down Integration for Snowflake – Joint DataRobot and Snowflake customers can benefit from the automatic discovery and computation of new features for their models directly in the Snowflake Data Cloud.
  • Time Series Eureqa Model Enhancements – DataRobot Automated Time Series now runs its unique Eureqa forecasting models as part of the regular Autopilot process. Eureqa models are based on the idea that a genetic algorithm can fit different analytic expressions to trained data and return a mathematical formula as a machine learning model.
  • No-Code AI App Builder  the No-Code AI App Builder allows customers to quickly turn any deployed model into a rich AI application without a single line of code.

Additional product upgrades: Data Prep for Time Series, Nowcasting for Time-Aware Models, Automated AI Reports, and Prediction Jobs and Scheduling UI.

Amplitude unveils experimentation application for digital optimization

Amplitude, a Digital Optimization System, introduced Amplitude Experiment, an experimentation solution combining customer behavior and product analytics. Amplitude Experiment provides organizations an end-to-end experimentation and delivery workflow that integrates customer data into every step from generating a hypothesis to targeting users to measuring results. Organizations can run higher impact A/B tests and remotely configure experiences for key segments. 

Organizations can get stuck in low-value activities that don’t drive growth, like testing small tweaks to copy and color changes or using basic on/off toggling to manage new feature release risk, or they waste resources and time on experiments that are doomed to fail, like starting from a weak hypothesis or not being able to reach the right segments. The Behavioral Graph and Amplitude’s Digital Optimization System, Amplitude Experiment addresses these challenges by resolving the underlying issues of experiment design, targeting, identity resolution and analysis. With the Amplitude Experiment solution, organizations have a complete learning and growth loop from insight to action to testing and delivery in a single system. 

  • Amplitude Analytics identifies problems, uncovers opportunities, and measures impact. 
  • Amplitude Recommend matches the right messages, content, and items to each individual user.
  • Amplitude Experiment tests bets and serves the best experience to customers.

Snowflake adds features

Snowflake unveiled new product innovations for the Data Cloud, including data programmability, global data governance, and platform optimizations.

Data programmability:

  • Snowpark. With initial support for Java and Scala, Snowflake’s developer experience, Snowpark, allows data engineers, data scientists, and developers to build using their preferred language and execute these within Snowflake.
  • Java UDFs. With Java user-defined-functions (UDFs), customers can bring their custom code and business logic to Snowflake.
  • Unstructured data. Snowflake’s unstructured data support enables customers to store, govern, process, and share file data alongside their structured and semi-structured data.
  • SQL API. The Snowflake SQL API enables applications to call Snowflake directly through a REST API.

Global governance:

  • Classification. Snowflake’s classification capability automatically detects personally identifiable information (PII) in a given table and leverages the tagging framework to annotate the data.
  • Anonymized views. This can be used to protect privacy and identity in a dataset.


  • Improved Storage Economics. Better compression, and reduced storage costs.
  • Improved Support for Interactive Experiences. Updates released for high volume and low latency workload requirements improve query throughput on a single compute cluster.
  • Usage Dashboard. New usage dashboard helps customers better understand usage and costs across the platform.

GraphDB 9.8 brings text mining and Kafka connectivity

Ontotext announced the realize of GraphDB 9.8, which offers text mining integration, notifications over Kafka, Helm charts, and performance improvements. The text mining plugin comes with out-of-the-box support for text analytic services such as Ontotext’s Tag API, GATE Cloud, and spaCy server, as well as an expressive mapping language, to register new services without coding. The extracted text annotations can be manipulated with SPARQL and either returned to the caller for further processing or stored directly into the repository where they will enrich the existing knowledge graph. This functionality covers a number of use-cases that rely on both RDF and text analytics.

The Kafka connector provides a means to synchronize changes to the RDF model to any downstream system via the Apache Kafka framework. Each Kafka connector instance will stay automatically up-to-date with the GraphDB repository data. The implementation is built on the same framework as the existing Elasticsearch, Solr and Lucene connectors and allows for precise mapping from RDF to JSON, such as defining fields based on property chains, nested document support as well as advanced filtering by type, literal language or a complex expression. GraphDB 9.8 comes with standard Helm charts and instructions that can help you get started with GraphDB Enterprise Edition on Kubernetes.

Kofax updates Intelligent Automation Platform

Kofax, a supplier of Intelligent Automation software for digital workflow transformation, announced the latest release of its Intelligent Automation Platform. Kofax TotalAgility, the workflow orchestration engine within the company’s Intelligent Automation Platform, has been enhanced with 50 new low-code, document intelligence, process orchestration and connected systems capabilities.

  • Faster development of automation workflows. A new user experience extends low-code to more business users by empowering citizen developers and analysts to easily setup complex workflows. An enhanced business rules engine allows analysts to execute decision strategies by using visual condition rules and setting up custom services without needing to code.
  • Expanded low-code support for cognitive capture. Nearly 90 percent of data generated today is unstructured. Kofax’s cognitive capture functionality enables professional developers to build advanced AI and Capture models, allowing them to train the system and effectively incorporate document intelligence.
  • One-click document classification. Kofax TotalAgility enables citizen developers and business analysts to enhance advanced document classification models, empowering them to rapidly and visually train, identify and classify documents.
  • Additional low-code integration options. Simplified integrations include new support for OpenAPI and grouping of data, enabling data models to be defined manually or using simple JavaScript Object Notation (JSON). Enhanced support for industry-standard OAuth 2.0 provides greater authorization and authentication options.

Docebo adds learning analytics to Multi-product Suite

Docebo, an artificial intelligence (AI)-powered learning suite, announced the launch of Docebo Learning Analytics, the newest addition to its multi-product learning suite. Docebo Learning Analytics is a business intelligence tool that allows enterprise customers to retrieve, analyze, and transform the data from their learning programs into useful business insights. With Docebo Learning Analytics, L&D professionals around the world will be able to better tie the results of their training programs back to business outcomes to make the most strategic decisions for their business. In March 2021, the company launched Docebo Learning Suite to address the full enterprise learning lifecycle to give customers the ability to create, manage, deliver, and measure the business impact of learning. Together with products Docebo Learn LMS, Shape, Content, and Learning Impact—Docebo Learning Analytics will allow organizations to close the loop by proving their learning programs are powering their business.

Microsoft Build — selected news

Lots of news this week at the annual Microsoft Build developer conference. They did produce a very helpful “Book of News” (at about 8,800 words) with a table of contents to cover it all. Below is a selection of announcements our readers are most likely to be interested in, followed by a link to the complete list.

Azure AI

Azure Cognitive Services, a family of AI services to deploy high-quality models as APIs, has multiple updates, including:

  • Document Translation, a feature of Translator in Azure Cognitive Services announced in preview in February, is now generally available. Document Translation enables developers to quickly translate documents while preserving the structure and format of the original document. This feature helps enterprises and translation agencies that require the translation of complex documents into one or more languages.
  • Text Analytics for health is now generally available with Text Analytics in Azure Cognitive Services. It enables developers to process and extract insights from unstructured medical data. Unstructured text includes doctors’ notes, medical journals, electronic health records, clinical trial protocols and more. Another new feature of Text Analytics is Question Answering. Now in preview, Question Answering helps users find answers from a passage of text without saving or managing any data in Azure.

Azure Data

With the introduction of the partial document update for Azure Cosmos DB, developers can modify specific fields or properties within a document without requiring a full document read and replace. This gives developers more flexibility to update only certain portions. Partial document update is available for Core (SQL) API and via .NET SDK, Java SDK and stored procedures. Developers can sign up for the partial document update preview.

Azure Cosmos DB serverless is now generally available for all APIs (Core, MongoDB, Cassandra, Gremlin and Table). Developers can now optimize costs and more easily run apps with spiky traffic patterns on Azure Cosmos DB. Serverless is a cost-effective pricing model that charges only for the resources consumed by database operations. It is ideally suited for apps with moderate performance requirements and frequent periods with little to no traffic.

Microsoft 365

Microsoft Graph data connect is now offered on Microsoft Azure as a metered service. Microsoft Graph data connect is a more secure, high-throughput connector designed to copy select Microsoft 365 productivity datasets into the Azure tenant. It’s a tool for developers and data scientists creating organizational analytics or training AI and machine learning models. Although most Microsoft 365 products are offered on a per-user/per-month basis, the company is offering Microsoft Graph data connect as a metered service, so developers pay for only the data they consume.

Microsoft Search Federation, which connects information from across platforms, will be generally available later this year. It creates a unified search experience across Microsoft Azure Cognitive Search and Dynamics 365. Microsoft 365 customers use several search options, from Microsoft Search to Azure Cognitive Search. Microsoft Search Federation connects these systems, making finding information much simpler.

Microsoft Teams

Microsoft Teams apps for meetings, launched last year, gives developers the tools to build collaborative apps that help connect people to solve common goals and design experiences across the full lifecycle of a meeting. Now, developers can build even more unique scenarios with new features that include:

  • Shared stage integration, in preview, provides developers with new access to the main stage in a Teams meeting through a simple configuration in their app manifest. This provides a new surface to enable real-time, multiuser collaboration experiences for their meetings apps, such as whiteboarding, design, project boards and more.
  • New meeting event APIs, in preview, enable the automation of meeting-related workflows through events, such as meeting start and end, with many more planned for later this year.
  • Together mode extensibility, coming soon, empowers developers to create custom scenes for Teams meetings and share them with users. This provides an easy design experience, within the Developer portal, so developers can make meetings more engaging.
  • Media APIs and resource-specific consent, coming soon, provide developers with real-time access to audio and video streams for transcription, translation, note-taking, insights gathering and more.

Fluid components in Microsoft Teams chat is now in private preview and will expand to more customers in the coming months. Fluid components are powered by the web, can be edited in real-time or asynchronously and work across surfaces, such as Teams and Office apps. Fluid components in Teams chat allow users to send a message with a table, action items or a list that can be co-authored and edited by everyone in line, minimizing the need for long chat threads and meetings. Fluid components can be copied and pasted across Teams chats, helping users become more efficient.

Power Platform

Microsoft Power Fx, a low-code open-source programming language, is adding new features that allow developers to build apps using natural language — no coding required.

The new experience centers around three key scenarios: natural language transforms to Power Fx code, Power Fx code transforms to natural language and programming by example where a user inputs an example of a data pattern that trains the model.

This experience is powered by GPT-3, the world’s largest natural language model from OpenAI, running on Azure Machine Learning. Microsoft also is announcing the PROgram Synthesis using Examples SDK (PROSE), which can train models to do certain tasks by typing in a few examples.

Microsoft Power BI users can now embed Microsoft Power BI analytics reports in a Jupyter Notebook. Jupyter Notebook, an open-source development tool featuring documents with live code, equations, visualizations and narrative text, is often used for data visualization and more. Power BI Embedded Analytics enables data app developers to engage directly with data, explore analytics and generate reports. These Jupyter Notebook integrations are now in preview.

Power BI Premium, which enables analysts, developers and business users to create, develop and turn data into insights, has added Automation APIs to its deployment pipeline capabilities. This allows developers to use tools, such as Microsoft Azure DevOps and Azure Pipeline, to automate the deployment of Power BI assets and integrate into their existing app deployment framework.

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