Curated for content, computing, and digital experience professionals

Month: February 2021 (Page 2 of 5)

Gilbane Advisor 2-18-21 — graphs, stacks, apps, meshes, privacy

In this issue we look at enterprise knowledge graph semantics, how to move to a distributed data mesh, a helpful case study on UX improvements, “best-of-breed” stacks, and personal data privacy, first party ads, and consumer contradictions.

A definition of “Enterprise” in EKGs

Enterprise knowledge graphs are on the rise, but terminology and even conceptual understanding is inconsistent. Dan McCreary’s article is a good place to start to organize your own thoughts before diving in…

Many people co-mingle the terms from open linked data world and the semantic web stack’s role with the concepts related to sustainability and scalability of enterprise knowledge graphs.

How to move beyond a monolithic data lake to a distributed data mesh

If you haven’t yet had a reason to develop a complete understanding of what a distributed data mesh is, or how it relates to looking at data as a product for multiple enterprise functions, there is a good chance you will before long. Some familiarity will be important for many roles beyond pure data management. This in-depth article by Zhamak Dehghani covers the why and how, and likely answers most questions you have.

Quantifying UX improvements

Nielsen Norman Group’s Kate Moran presents a case study, with before and after screen shots and metrics, illustrating how an informed information architecture can increase customer self-service and improve both customer experience and sales efficiency.

Best-of-breed stacks

Debates on the relative merits of vendor suites versus best-of-breed application solutions have been going on for decades. The data was scarce and questionable, the arguments “qualitative”, and the conclusions invariably “it depends…”.

Scott Brinker has a lot to say about today’s version of this debate with the more complicated and flexible software architecture options available. For his latest post on the topic he came up with a great way to apply some neutral data to his view that stacks are growing and increasingly best-of-breed.

Also, on personal data, privacy, ads…

The Gilbane Advisor is curated by Frank Gilbane for content technology, computing, and digital experience professionals. The focus is on strategic technologies. We publish more or less twice a month except for August and December. We also publish curated content technology news weekly We do not sell or share personal data.

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Alation releases update to data intelligence platform

Alation Inc., provider of enterprise data intelligence solutions, announced the release of Alation 2021.1. The newest release extends connector and query coverage to virtually any data source, expedites relevant search & discovery through data domains, and features new data governance capabilities.

Alation 2021.1 includes connectors to a comprehensive range of applications and data sources, beyond Business Intelligence (BI) and filesystems, to applications such as ServiceNow and Salesforce. The platform’s new, federated authentication enables users to query cloud services such as Amazon Web Services (AWS) and Snowflake using single sign-on. By snapping into a variety of applications and data sources, Alation serves as a single place to find, understand, and trust data across an organization. Alation 2021.1 also includes:

  • Accelerated time to insight. A new Open Connect Framework software development kit (SDK) enables third parties, including customers and partners, to build connectors to niche RDBMS and BI data sources such as NoSQL and application sources.
  • Increased search relevancy by allowing users to narrow their searches based on how data is grouped logically by the organization, such as business unit or geography.
  • New data governance capabilities. New impact analysis reports provide an immediate view into the downstream impact of data changes.

WP Engine available in AWS Marketplace

WP Engine, a WordPress technology company, announced availability in AWS Marketplace. WP Engine is committed to being a catalyst for digital experiences on WordPress by combining proprietary technology with a modern tech stack. By leveraging AWS, WP Engine enables brands to quickly build and launch fast, secure digital experiences with insights to maximize consumer engagement.

WP Engine’s collaboration with AWS began in 2015 and spans from the core platform infrastructure to WordPress ecosystem products like Amazon Polly integration, AWS Digital Customer Experience Competency status, and now availability in AWS Marketplace. WP Engine offers a range of enterprise-grade, high-resiliency, high-availability solutions on WordPress-optimized AWS architecture. With AWS’s global regions and multi-zone redundancy across all traffic-serving layers, customers benefit from the best uptime protection and risk mitigation with the elimination of single points of failure on the WP Engine WordPress digital experience platform.

Patra and partner on natural language understanding for insurance

Patra, a provider of technology-enabled services for the insurance industry, and, an artificial intelligence solution for natural language understanding and natural language processing (NLU/NLP), announced a partnership that brings efficiencies to a variety of insurance processes. This partnership delivers AI-powered policy checking to the insurance market. By combing’s technology and expertise along with the market power of the InsurConneXtions Alliance members, additional complex solutions are currently being developed for the industry. enables global organizations to leverage its AI-based natural language (NL) platform to automate the reading, understanding, and extraction of meaningful data from structured and unstructured text to augment and expand insights for every process that involves language. By integrating’s AI capabilities, Patra will improve quality, reduce friction, and drive out inefficiencies in the process of manually reviewing and cross-validating dozens to hundreds of pages of text for any given policy. These capabilities will facilitate a deeper understanding of data, enabling previously out-of-reach insights due to the vast and complex nature of language semantics. With close to 80% of the information within the insurance industry being unstructured data, intelligent automation based on human-like understanding is a critical factor for increasing capacity, and reducing inefficiencies and high-risk vulnerabilities.,

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Franz announces Allegro NFS Server 7.0 for Windows

Franz Inc., supplier of graph database technology for knowledge graph solutions, announced Allegro NFS Server 7.0 for Windows with 64-bit performance and support for all current versions of the Windows operating system. Allegro NFS Server 7.0 delivers a high performance, easy-to-install solution for small and large enterprise-wide deployments. Allegro NFS was originally developed for Franz’s internal purposes due to dissatisfaction with free and commercial NFS Servers available on the market and the incredible technical difficulties faced in configuring them on Windows. Since 2002, Allegro NFS has been adopted by many Fortune 500 companies who want reliable and easy-to-configure access to Windows from NFS clients.

Allegro NFS Server 7.0, runs on all the current versions of the Windows operating system including Vista, Server 2003, Server 2008, Server 2012, Windows 7 (32 and 64-bit), Windows 8 (32 and 64-bit), and Windows 10 (32 and 64-bit). Allegro NFS also has version that to run on Windows XP. To evaluate or purchase Allegro NFS Server 7.0, go to,

Apache announces Apache Gobblin as a Top-Level Project

The Apache Software Foundation (ASF) announced Apache Gobblin as a Top-Level Project (TLP). Apache Gobblin is a distributed Big Data integration framework used in both streaming and batch data ecosystems. The project originated at LinkedIn in 2014, was open-sourced in 2015, and entered the Apache Incubator in February 2017. Apache Gobblin is used to integrate hundreds of terabytes and thousands of datasets per day by simplifying the ingestion, replication, organization, and lifecycle management processes across numerous execution environments, data velocities, scale, connectors, and more.

As a scalable data management solution for structured and byte-oriented data in heterogeneous data ecosystems, Apache Gobblin makes the task of creating and maintaining a modern data lake easy. It supports the three main capabilities required by every data team:

  • Ingestion and export of data from a variety of sources and sinks into and out of the data lake while supporting simple transformations.
  • Data Organization within the lake (e.g. compaction, partitioning, deduplication).
  • Lifecycle and Compliance Management of data within the lake (e.g. data retention, fine-grain data deletions) driven by metadata.

Apache Gobblin software is released under the Apache License v2.0 and is overseen by a self-selected team of active contributors to the project. A Project Management Committee (PMC) guides the Project’s day-to-day operations, including community development and product releases.

DataRobot announces Feature Discovery integration with Snowflake

DataRobot announced the latest integration with Snowflake. Building off of DataRobot’s expanded partnership and existing integration with Snowflake, the new Feature Discovery pushdown integration improves the speed and accuracy of developing models, unlocking new use cases. DataRobot’s Feature Discovery, which has been a part of the DataRobot enterprise AI platform since 2019, automatically discovers, tests, and creates hundreds of valuable new features for machine learning models. This improves models’ accuracy, increasing an organization’s ability to make accurate predictions.

The new Feature Discovery integration with Snowflake delivers this capability to Snowflake users, pushing down data preparation operations into Snowflake to minimize data movement resulting in faster performance and lower operating costs. This allows users to obtain more accurate DataRobot models by accessing more data from Snowflake and leveraging the power of Snowflake’s Data Cloud. With Feature Discovery, the joining, aggregating, and creation of derived features from datasets is done automatically using data science best practices. This lets users build better machine learning models in less time and drive more innovation with AI.

Elcom updates digital experience platform

Elcom, a Digital Experience Platform used to deliver digital-first strategies through intranets, digital workplaces, websites, and portals, announced the launch of Elcom V11.5. The Elcom team has enhanced the design and usability of the platform. Administrators and publishers have more choice and control around the management, delivery, and access of content-related experiences, while audiences will have greater flexibility in how they interact with these sites. The latest version provides:

  • Enhanced publishing and authoring experience. End users can publish articles by filling out a form and selecting new article attributes and metadata options. Publishers can also quickly change layouts and share drafts with external stakeholders securely.
  • Design and usability of dynamic widgets. Highlights include the ability to show featured articles, custom metadata to increase search options, and the ability to favourite content directly from a widget.
  • More flexibility with the forms tool. Highlights include the ability to pull in data from external sources, improved form validation rules and rendering on mobile.
  • Streamlined and automated processes with workflows for forms and content.
  • Additional mechanisms to keep data safe and secure. Including enhanced password security checks, new reports for administrators, and the ability to add reports in dashboards.

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