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Category: Computing & data (Page 29 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.

Searchable.ai announces Constellation

April 28, 2022 /

Searchable.ai announced Constellation, their unified data platform that brings together all the data and information that knowledge workers and teams need in one place. While Searchable.ai initially focused on unifying data and information from files, such as those created with Microsoft Office and Google Workspace apps, as well as PDFs, Constellation makes it possible to unify user-inputted SaaS data. Structured information from Jira tickets and Trello cards, for example, as well as conversations in apps like Slack, can now be searchable and shareable. Additionally, Constellation’s Live Sync technology means data is constantly being updated and refreshed, so users always have access to the latest information.

Constellation supports an unlimited amount of data and is engineered with enterprise-grade security. Eventually, Searchable.ai will enable developers to access the Constellation framework for their own apps and services, including corporations who may want to ingest this data into their own repositories.

For now, Searchable.ai will leverage Constellation to extend its end-user capabilities beyond search. The company will soon be releasing Collections, a way for users to assemble groups of files, email, and cloud data in a central space where others can add, find, and access what they need for their work.

https://www.searchable.ai/post/announcing-constellation

Expert.ai updates AI-based natural language processing platform

April 26, 2022 /

Expert.ai announced the new release of its platform combining symbolic, human-like comprehension and machine learning to turn language into data, analyze and understand complex documents, accelerate intelligent process automation and improve decision making. By extending core features and adding unique capabilities, such as out of the box knowledge models and connectors, the new release increases flexibility, simplifies integration and optimizes data pipelines to augment efficiency across every process that involves natural language (NL).

Specifically designed for natural language AI, the expert.ai platform leverages the combination of different AI techniques (machine learning and rule-based symbolic comprehension) with a simple and powerful authoring environment to support the full natural language processing workflow. It is based on the principle that no single natural language AI technique is a fit for every project. The new release includes:

  • ‘Smarter from the start’ knowledge models deliver NL applications to production faster with higher levels of business accuracy
  • Simplified deployment processes across multiple environments, including Azure
  • Easier integration, out of the box connectors
  • Enhanced natural language operations: provides the ability to include custom Python and Java scripts or third-party services for pre- or post-processing activities in NL workflow orchestrations.

https://www.expert.ai

Akamai launches Linode managed database

April 25, 2022 /

Akamai Technologies Inc., launched a managed database service powered by Linode with support for MySQL, PostgreSQL, Redis, and MongoDB. Akamai’s Linode Managed Database simplifies database deployment, helping developers reduce risk, increase efficiency, and minimize the complexity that comes with manual management of production database clusters.

The launch of Linode Managed Database service marks Akamai’s first product launch in its compute line of business following its acquisition of Linode in March of this year, to further its mission to develop a distributed compute platform from cloud to edge.

With Akamai’s Linode Managed Database service, users can defer common deployment and maintenance tasks to Linode and elect high availability configurations to ensure that database performance and uptime are never affected. The result: less hands-on management expertise is required to deploy applications and a decreased risk of downtime compared to manual management.

At launch, Akamai will offer Linode Managed Database for MySQL in all of Linode’s 11 global data centers, with support for PostgreSQL, Redis, and MongoDB to follow in the second quarter of 2022. With each supported managed database, customers can take advantage of features such as flat-rate pricing, security and recovery measures, flexible deployment options, and high availability cluster options.

https://www.linode.com ■ https://www.akamai.com

Databricks announces lakehouse offering for media and entertainment

April 21, 2022 /

Databricks launched a lakehouse platform for data-driven businesses in the media and entertainment industry. The Lakehouse for Media & Entertainment enables organizations across the media ecosystem to deliver better data and AI outcomes for consumers, advertisers and media partners with a single and collaborative platform for data, analytics, and AI. Databricks is also working with Amazon Web Services (AWS) and industry partners like Cognizant, Fivetran, Labelbox and Lovelytics.

With use case accelerators, custom Brickbuilder Solutions and a partner ecosystem, businesses will be able to deliver a personalized consumer experience, prepare for consumer analytics, and provide collaboration and secure data sharing among media teams. The Lakehouse for Media and Entertainment incorporates data solutions and accelerators for use cases like AI-driven recommendation engines, customer lifetime value and churn, quality of experience, community toxicity analysis, and advertising optimization.

With Databricks, organizations can leverage all of their data to build a holistic view of their audience and advertisers, make real-time decisions and drive innovation with advanced analytics. With business intelligence (BI), and AI capabilities on all data types, Databricks enables media organizations to use all of their data – including images, video and other unstructured data types – to develop a holistic understanding of their customers.

https://databricks.com/company/newsroom/press-releases/databricks-announces-lakehouse-offering-for-customers-in-the-media-and-entertainment-industries

Element announces Connector Portal, Unify Graph, and Advanced Joins

April 19, 2022 /

Element, a software provider in IT/OT data management for industrial companies, announced new functionality for simplified connections, knowledge graph-based modeling, and advanced joins. Together they increase flexibility and speed up model development for organizations seeking to deploy digital twins or pursue industrial transformation.

The Connector Portal provides access to pre-built connectors for a range of commonly-used data sources and consuming targets, speeding analytics projects by reducing manually establishing connections. The portal also provides a connector framework that developers can use to build their own custom connectors.

Unify Graph brings a knowledge graph approach to bear for mapping the complex data environments typical at most enterprises that data teams must operate across. It allows flexible data modeling spanning arbitrary dimensions such as processes, assets, organizations necessary for building effective digital twins. The graphs can be queried and explored within Unify or exported for consumption by graph database products such as AWS Neptune or Neo4j.

The Advanced Joins functionality enables users to combine data from various sources based on matching multiple relevant data fields and using matching approaches. The fuzzy matching approach is configurable and allows the user to specify a similarity threshold for deciding matches.

https://www.elementanalytics.com

dbt Labs announces availability on Databricks Partner Connect

April 14, 2022 /

Analytics engineering tool supplier dbt Labs announced the availability of dbt Cloud on Databricks Partner Connect. Databricks customers now have a fast and frictionless way to experience the benefits of dbt Cloud on the lakehouse. dbt has become popular for data transformation with demand largely driven by the industry-wide shift to cloud-based data platforms like Databricks. It enables data teams to transform data in-warehouse, and deploy analytics code following software engineering best practices.

Through Databricks Partner Connect, all Databricks users will now have the ability to quickly provision a new dbt Cloud trial that is pre-connected to their Databricks account. In just a few clicks, users will be set up with a dbt Cloud account – ideal for those looking to quickly get a feel for what the two can achieve together through a streamlined, pre-configured workflow. Also:

  • Databricks has developed a new, dedicated dbt-Databricks adapter, bringing an easier installation process and a more optimized performance.
  • Databricks Ventures participated as a strategic investor in dbt Labs’ Series D funding round in February 2022.
  • There are more than 1,000 members of the Databricks and Spark channel within the dbt Community Slack

https://www.getdbt.com ■ https://databricks.com/partnerconnect

MongoDB announces pay-as-you-go on Google Cloud

April 12, 2022 /

MongoDB, Inc., a general purpose database platform, announced the launch of a pay-as-you-go MongoDB Atlas offering, which can be launched directly from the Google Console. The offering provides developers with a simplified subscription experience, and enterprises more choice in how they procure MongoDB on Google Cloud. Customers only pay for the resources they use and can scale based on their needs, with no up-front commitments while using their Google accounts. This offering will also make it easier for customers to build, scale, and manage data-rich applications with MongoDB Atlas within the Google Cloud Console.

MongoDB enables developers to integrate Atlas with Google Cloud products including BigQuery, Apigee, Tensorflow, Cloud Run, App Engine, EventArc, Cloud Functions, DataStream, Google Kubernetes Engine (GKE), Dataproc, Dataflow, and Pub/Sub. In addition to these offerings, MongoDB and Google Cloud have expanded their joint reach across 28 global regions, including the recent availability in Toronto and Santiago. Previously applicable only to migrations from RDBMS to cloud-based RDBMS, migVisor is now available for MongoDB On-Premises to MongoDB Atlas migrations.

https://investors.mongodb.com/news-and-events/news-releases/news-details/2022/MongoDB-Announces-a-Pay-As-You-Go-Offering-on-Google-Cloud/default.aspx

Google announces BigLake, to unify data lakes and data warehouses across clouds

April 6, 2022 /

From the Google Cloud blog…

The volume of valuable data that organizations have to manage and analyze is growing at an incredible rate. This data is increasingly distributed across many locations, including  data warehouses, data lakes, and NoSQL stores.

Today, we’re excited to announce BigLake, a storage engine that allows you to unify data warehouses and lakes. BigLake gives teams the power to analyze data without worrying about the underlying storage format or system, and eliminates the need to duplicate or move data, reducing cost and inefficiencies. With BigLake, users gain fine-grained access controls, along with performance acceleration across BigQuery and multicloud data lakes on AWS and Azure. BigLake also makes that data uniformly accessible across Google Cloud and open source engines with consistent security. BigLake enables you to:

  • Extend BigQuery to multicloud data lakes and open formats such as Parquet and ORC with fine-grained security controls, without needing to set up new infrastructure.
  • Keep a single copy of data and enforce consistent access controls across analytics engines of your choice, including Google Cloud and open-source technologies such as Spark, Presto, Trino, and Tensorflow.
  • Achieve unified governance and management at scale through seamless integration with Dataplex.

https://cloud.google.com/blog/products/data-analytics/unifying-data-lakes-and-data-warehouses-across-clouds-with-biglake

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