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Category: Computing & data (Page 27 of 80)

Computing and data is a broad category. Our coverage of computing is largely limited to software, and we are mostly focused on unstructured data, semi-structured data, or mixed data that includes structured data.

Topics include computing platforms, analytics, data science, data modeling, database technologies, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing applications such as machine translation, and knowledge graphs.

Related categories: Semantic technologies, Web technologies & information standards, and Internet and platforms.

Snowflake launches Unistore

June 14, 2022 /

Snowflake announced the launch of Unistore, a new workload that expands the capabilities of Snowflake and delivers a modern approach to working with transactional and analytical data together in a single platform. Unistore extends the Snowflake Data Cloud to streamline and simplify the development of transactional applications, while providing consistent governance, performance, and scale to customers.

Transactional and analytical data have typically been siloed, creating complexities when moving data between systems and hindering the speed required for modern development. With Unistore, teams can expand the Data Cloud to include transactional use cases such as application state and data serving. As a part of Unistore, Snowflake is introducing Hybrid Tables, which offer fast single-row operations and allow customers to build transactional business applications directly on Snowflake. Hybrid Tables, currently in private preview, enable customers to perform swift analytics on transactional data for immediate context, and join Hybrid Tables with existing Snowflake Tables for a holistic view across all data. Unistore and Hybrid Tables enable customers to build transactional applications with the same simplicity and performance they’re used to with Snowflake, and a unified approach to data governance and security.

https://www.snowflake.com/blog/introducing-unistore/

Adobe announces new Adobe Analytics services

June 14, 2022 /

Adobe announced new services in Adobe Analytics, delivering a single workspace for brands to unify data and insights across all media types. Adobe also introduced a new service to transition data from other analytics products while preserving historical compliance with regulations such as Global Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA).

Streaming media: Adobe is introducing new capabilities for brands to understand how streaming fits into the overall customer journey. Through Customer Journey Analytics (CJA), teams can tie digital media consumption to engagement on other channels like social media, websites and offline channels.

Seamlessly bring data together: With the bulk data insertion API now available, teams can move or activate any volume of historical data into Adobe Analytics. It covers any online or offline channel, allowing brands to transition data sources from point-of-sale devices, CRM systems and mobile applications.

Intelligent data mapping: Adobe Analytics is providing flexibility for brands to bypass the data migration preparation work while avoiding data destruction. As data comes through, Adobe Analytics preserves the underlying structure, and also suggests new ways to measure the customer journey. Brands can also retroactively apply dimensions to historical data, such as new attribution models.

https://news.adobe.com/news/news-details/2022/Next-Generation-Adobe-Analytics-Delivers-Customer-Insights-From-Streaming-Media-and-the-Metaverse/default.aspx

MongoDB unveils vision for a developer data platform

June 7, 2022 /

MongoDB, Inc. unveiled its developer data platform vision with new capabilities, helping development teams with a wider set of use cases, servicing more of the data lifecycle, optimizing for modern architectures, and implementing sophisticated levels of data encryption. MongoDB 6.0 has extended its approach of working with data beyond operational and transactional use cases to serve search and analytics use cases within a unified platform and consistent developer experience to reduce the complexity of data infrastructure required for modern applications. Upcoming capabilities include:

  • Making it easier for developers to leverage in-app analytics. Column Store Indexes will enable users to create and maintain a purpose-built index that speeds up many analytical queries without requiring changes to the document structure. 
  • Time series collections will support secondary indexes on measurements, and feature read performance improvements and optimizations for sorting time-based data more quickly.
  • With Search Facets, developers are able to rapidly build search experiences that allow end users to more seamlessly browse, narrow down or refine their results.

MongoDB also announced new products and capabilities that enable development teams to better analyze, transform, and move their data in Atlas while reducing reliance on batch processes and ETL jobs.

https://www.mongodb.com/new

Algolia launches additional AI models in Algolia Recommend

June 6, 2022 /

Algolia, an API-First Search & Discovery platform, unveiled additional AI (artificial intelligence) models and capabilities in its Recommend Spring Release 2022. Algolia Recommend introduces AI models powered by behavioral insights. When coupled with Algolia’s fast indexing capabilities, customers are able to immediately put their most relevant and up to date content into motion for end-users. From a single dashboard, merchandisers, digital content managers, or digital business leaders can choose the model that is right for them, deploy it, and track the results. The release includes:

  • Popular Trends – AI models that detects emerging trends based on users’ behavioral data as they interact with various brands, categories of products and content, and topics of interest.
  • Business Rules – Low-code/no-code functionality for controlling AI and activating unique business strategies. This provides greater flexibility for category merchandisers, online retail strategists, and content specialists to generate new recommendations.
  • Hybrid Recommend Engine – This is a combination of collaborative filtering algorithms and content-based filtering algorithms to increase the relevancy and accuracy of recommendations. Recommendations can be presented to users as the content-based data is indexed. Availability of behavioral information either at this initial stage or later can further help fine-tune and enrich the quality of recommendations.

https://www.algolia.com/about/news/new-ai-based-recommendation-models-overcome-cold-start-challenge/

Stardog updates enterprise knowledge graph platform

June 2, 2022 /

Stardog, an Enterprise Knowledge Graph platform provider, unveiled Stardog 8.0, with new innovations to streamline data exploration and discovery for all citizen data users.

The new Advanced Query tool in Stardog Explorer empowers citizen data users to ask complex business questions via the semantic layer more easily. By removing the need to learn a graph query language, users can self-serve from across their enterprise data landscape. Also new in Explorer is the ability to see what’s in your Stardog database by browsing data source and virtual graph metadata in the new Stardog Data Catalog graph. Additional updates include:

  • Project resources (imported CSV files and virtual graphs) can be previewed and refreshed to see updates in the data.
  • Enhanced support for project collaboration through exporting, importing, and duplicating projects.
  • Our new query profiler is available and shows you the query plan, allows you to interrupt slow queries, and can show you partial results.
  • Error notifications now stay displayed and the error text can be copied for troubleshooting.
  • A new Stardog Data Catalog graph is built from the metadata about data sources and virtual graphs within a Stardog database.
  • Improved performance for querying multiple virtual graphs and SPARQL update queries.

https://www.stardog.com/blog/introducing-stardog-8.0/

MariaDB and MindsDB collaborate on machine learning

May 31, 2022 /

MariaDB Corporation and MindsDB, a provider of in-database machine learning tools, together announced a technology collaboration that makes machine learning predictions easy and accessible to cloud database users.  By using MindsDB in SkySQL, MariaDB’s fully managed cloud database service, data science and data engineering teams can increase their organization’s predictive capabilities to plan for and address business issues. MariaDB database users will now be able to add machine learning based predictions directly into their datasets stored in SkySQL. This simplifies the task of analyzing and predicting future trends, putting machine learning capabilities into the hands of MariaDB users, no matter their role. The use cases for business predictions cut across every business function such as finance, sales, risk analysis, logistics, operations, and marketing.

https://mindsdb.com ■ https://mariadb.com/products/skysql/

SimInsights launches no-code XR authoring platform

May 30, 2022 /

SimInsights announced general availability (GA) of HyperSkill, a no-code 3D simulation software for Virtual and Augmented Reality and Artificial Intelligence powered training. HyperSkill was created to enable instructional designers and subject matter experts to author immersive, interactive and intelligent training content without having to learn programming or technical skills in machine learning and artificial intelligence. HyperSkill enables non-programmers to author VR/AR/AI-powered content, automatically optimize it and publish it across many devices and audiences and collect and visualize experience data for assessment and evaluation. HyperSkill has been used by customers in healthcare, manufacturing and education and has been developed with their close collaboration and feedback. HyperSkill includes:

  • No-code authoring: Faster and cheaper to author compared to programming with 3D game engines
  • Reusable repository: Growing public repository of XR-ready 3D assets, including virtual environments, virtual persons and virtual objects
  • AI-Powered: Natural Language Processing (NLP) and Computer Vision to simplify authoring, enhance experiences and unlock new use cases
  • Cross Platform: Author once, deliver everywhere, including emerging AR/VR headsets as well as web, desktop and mobile platforms.
  • Multiplayer: Enables synchronous learning scenarios, including collaborative and instructor-led training.

HyperSkill is a SaaS (Software as a Service) product available for a free trial.

https://siminsights.com/hyperskill/

Deepnote data notebook comes out of beta

May 26, 2022 /

Deepnote, an early-stage startup backed by Accel and Index Ventures, launched version 1.0, opening up to the general availability of collaborative data science notebooks to data teams. Data team efficacy relies on the process of access to, exploration of, and collaboration around data—for example, when an organization needs to make a data-informed decision, it will rely on data teams to explore datasets and share insights that lead to action. This process is siloed within a single department, findings are inconsistent, and insights quickly become out of date. Deepnote makes data collaboration a reality improving three pain points of traditional data science notebooks:

  1. Collaboration: Sharing analysis and collaboration is as easy as sending a link because everything is hosted in a fully-managed cloud environment. Analysis is done in real-time with multiplayer mode if needed. And everything is organized and hosted in a single place.
  2. Connectivity: With dozens of native integrations to tools in the modern data stack—Snowflake, BigQuery, Postgres, S3, GitHub—data teams can seamlessly connect to the tools they’re already using.
  3. Productivity: Underserved data analysts and scientists are now equipped with productivity features—reproducibility, autocomplete, scheduling, version control—to do better work in less time.

https://deepnote.com/

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