Wednesday, March 7, 2018

Allegro "Knowledge" Graph News - March 2018


In this issue

Webcast - Navigating Time and Probability in Knowledge Graphs
Thursday, March 22 at 11AM Pacific
The market for knowledge graphs is rapidly developing and evolving to solve widely acknowledged deficiencies with data warehouse approaches. Graph databases are providing the foundation for these knowledge graphs and in our enterprise customer base we see two approaches forming: static knowledge graphs and dynamic event driven knowledge graphs.
Static knowledge graphs focus mostly on metadata about entities and the relationships between these entities but they don’t capture ongoing business processes. DBPedia, Geonames and Census or Pubmed are great examples of static knowledge. Dynamic knowledge graphs are used in the enterprise to facilitate internal processes, facilitate the improvement of products or services or gather dynamic knowledge about customers.
Dr. Aasman recently authored an IEEE article describing this evolution of knowledge graphs in the Enterprise and during this presentation we will describe two critical success factors for dynamic knowledge graphs, a uniform way to model, query and interactively navigate time and the power of incorporating probabilities into the graph. The presentation will cover three use cases and live demos showing the confluence of knowledge via machine learning, visual querying, distributed graph databases, and big data not only displays links between objects, but also quantifies the probability of their occurrence.
To register for this webinar, see here
The IEEE Paper Link

Webcast - A Juypter Notebook for Learning AllegroGraph (Bonus n-Dimensional GeoSpatial)

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.
Join us to learn more about the examples available with AllegroGraph's new Python tutorial using Jupyter Notebook for interactive learning.

To register for this webinar, see here

InfoWorld article - The marvels of an event-based schema
When working with various data types at the speed of big data, this method is ideal for integrating and aggregating assorted information for the holistic value it provides.
The issue of schema—and what is frequently perceived as its inherent difficulties—is becoming more important every day. Organizations are increasingly encountering decentralized computing environments typified by semi-structured or unstructured external data of varying formats, often requiring integration with internal, structured data for immediate business value...
To read the full article, see here

AllegroGraph 6.4.1 - Now Available
franz logo

New Features Include:

AllegroGraph Multi-master Replication is a real-time transactionally consistent data replication solution. It allows businesses to move and synchronize their semantic data across the enterprise. This facilitates real-time reporting, load balancing, and disaster recovery.

For additional information, see here

Gruff v7.2.1 - Now Available
gruff screen shot
New Features Include:
Gruff’s new 'Time Machine' feature provides users an important capability to explore temporal connections in your data. This capability lets you see how relationships are created over time and are you are able to replay the evolving graph for new temporal based insights."
Gruff produces dynamic data visualizations that organize connections between data in views that are driven by the user. This visual flexibility can instantly unveil new discoveries and knowledge that turn complex data into actionable business insights. Gruff was developed by Franz to address Graph Search in large data sets and empower users to intelligently explore graphs in multiple views including:
  • Graphical View with new “Time Machine” feature - See the shape and density of graph data evolve over time
  • Tabular view - Understand objects as a whole
  • Outline view - Explore the often hierarchical nature of graphs
  • Query view - Write Prolog or SPARQL queries
  • Graphical Query Builder - Create queries visually via drag and drop
For additional information, see the Gruff Documentation

IEEE Publication - Transmuting Information to Knowledge with an Enterprise Knowledge Graph
ITProfessional cover
The enterprise knowledge graph for entity 360-views has emerged as one of the most useful graph database technology applications when buttressed by W3C standard semantic technology, modern artificial intelligence, and visual discovery tools. Read this IEEE publication by Dr. Jans Aasman to learn more about Knowledge Graphs.

For additional information, see here

Enterprise Data World - Taking Graphs to the Next Level with Artificial Intelligence and Machine Learning - April 22-27, 2018
Text Analytics 17
The 22nd Annual Enterprise Data World (EDW) Conference hosted by DATAVERSITY® is recognized as the most comprehensive educational conference on data management in the world. Join hundreds of data professionals from around the globe to attend this unique conference. Your transformation to data-driven business starts here!
Franz CEO Jans Aasman will be presenting "Taking Graphs to the Next Level with Artificial Intelligence and Machine Learning".
Graphs and Knowledge Management have gained significant visibility with the rebirth of artificial intelligence and emergence of cognitive computing. By combining artificial intelligence, big data, graph databases, and dynamic visualizations, we will discuss deploying Graph based AI applications as a means to help predict future events across numerous types of industries.
Knowledge creation via AI and Graphs stems from the capability to combine the probability space (i.e. statistical inference on a user’s data) with a knowledge base of comprehensive industry terminology systems. AI using Graphs are remarkable not just because of the possibilities they engender, but also because of their practicality. The confluence of knowledge via machine learning, visual querying, graph databases, and big data not only displays links between objects, but also quantifies the probability of their occurrence. We believe this approach will be transformative across numerous business verticals.
During the presentation we will describe the Graph based AI concepts that also incorporate Hadoop, along with analytics via R, SPARK ML and other AI techniques for practical Enterprise predictive analytics use cases.
For additional information, see here

Franz Inc. - Named to Trend-Setting Products in Data and Information Management for 2018 by Database Trends and Applications
ODSC logo
Today, innovative approaches, such as Hadoop, Spark, NoSQL, and NewSQL, are being used in addition to more established technologies, such as the mainframe, and relational and MultiValue database systems. In addition, artificial intelligence and machine learning capabilities are some of the newer approaches being introduced in products. To help bring these resources to light, each year, Database Trends and Applications magazine looks for offerings that promise to help organizations derive greater benefit from their data, make better decisions, work more efficiently, achieve greater security, and address emerging challenges. In total, this list of forward-looking products helps illuminate the path on which the data management market is headed.
For additional information, see:

Analytics Week article - The Secret to Business Users Understanding Big Data: Enterprise Taxonomies
logo
The key to understanding big data doesn’t lie with some existent, or even forthcoming, application of Artificial Intelligence—although AI can certainly abet the process. Nor does it expressly relate to any facet of data science, blockchain, or decentralized computing application such as the Industrial Internet. Instead, the basis for modeling, integrating, governing, and even querying many of these manifestations of the data ecosystem lies with something much simpler: words.
Classifications of words and their hierarchies, taxonomies, are the rudiment to understanding big data’s meaning in terms business users comprehend. When such terminology systems span the enterprise, they create opportunities for the business to capitalize on big data’s underlying meaning, regardless of its form or the techniques used to access it...
To read the full article, see here

InfoWorld article - Harmonizing big data with an enterprise knowledge graph
logo
In addition to streamlining how users retrieve diverse data via automation capabilities, a knowledge graph standardizes those data according to relevant business terms and models.
One of the most significant results of the big data era is the broadening diversity of data types required to solidify data as an enterprise asset. The maturation of technologies addressing scale and speed has done little to decrease the difficulties associated with complexity, schema transformation and integration of data necessary for informed action...

To read the full article, see here

Dataconomy article - Triple Attributes: A New Way to Protect the Most Sensitive Information
Dataconomy logo
Semantic Graph Databases are now common in many industries, including life sciences, healthcare, the financial industry and in government and intelligence agencies. Graphs are particularly valuable in these sectors because of the complex nature of the data and need for powerful, yet flexible data analytics.
Attributes, user attributes and static filters are a new mechanism for graph databases to protect sensitive information. This combination provides the right amount of power and flexibility to address high-security use cases, such as: HIPAA access controls, privacy rules for banks, security models for policing, intelligence and the government. In addition, this set of methods is far easier to use, provides more expressiveness than security methods in relational databases and doesn’t suffer from performance degradations.
To read the full article, see here

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Tuesday, January 23, 2018

AllegroGraph v6.4 - Now Available

Release 6.4.0 is a major release with significant new features.

The most important and far-reaching change is support for multi-master replication

AllegroGraph has long supported single-master replication, where several AllegroGraph instances share data in a repository, but only one of them can make changes (adding or deleting triples). 

In multi-master replication, even though one instance is identified as the controlling instance, any instance can add or delete triples, with the remainder catching up with those changes while perhaps making other changes of their own. Single-master replication is still supported and is described in the Replication document. The new multi-master replication facility is described in Multi-master Replication.


AllegroGraph Multi-master Replication is a real-time transactionally consistent data replication solution. It allows businesses to move and synchronize their semantic data across the enterprise. This facilitates real-time reporting, load balancing, and disaster recovery.

Single repositories can be replicated as desired. The replicas each run in an AllegroGraph server. A single server can serve multiple replicas of the same repository (this is not typical for production work but might be common in testing). Note if there are multiple replicas in a single server, each replica must either be in a different catalog or must have a different name.

The collection of servers with replicas of a particular repository is called a replication cluster (or just cluster below in this document). Each repository in the cluster is called an instance. One instance is designated as the controlling instance, which will be described in more details below.

Each instance in the cluster can add or delete triples and these additions and deletions are passed to all other instances in the cluster. How long it takes for instances to synchronize depends on factors external to AllegroGraph (such as network availability and speed and whether the other servers are even available) but given time and assuming all instances are accessible, after a period of no activity (no additions or deletions) all instances will become synchronized.

Wednesday, December 20, 2017

AllegroGraph News - December 2017


In this issue

IEEE Publication - Transmuting Information to Knowledge with an Enterprise Knowledge Graph
ITProfessional cover
The enterprise knowledge graph for entity 360-views has emerged as one of the most useful graph database technology applications when buttressed by W3C standard semantic technology, modern artificial intelligence, and visual discovery tools. Read this IEEE publication by Dr. Jans Aasman to learn more about Knowledge Graphs.

For additional information, see here

Franz Inc. - Named to Trend-Setting Products in Data and Information Management for 2018 by Database Trends and Applications
ODSC logo
Today, innovative approaches, such as Hadoop, Spark, NoSQL, and NewSQL, are being used in addition to more established technologies, such as the mainframe, and relational and MultiValue database systems. In addition, artificial intelligence and machine learning capabilities are some of the newer approaches being introduced in products. To help bring these resources to light, each year, Database Trends and Applications magazine looks for offerings that promise to help organizations derive greater benefit from their data, make better decisions, work more efficiently, achieve greater security, and address emerging challenges. In total, this list of forward-looking products helps illuminate the path on which the data management market is headed.
For additional information, see:

Enterprise Data World - Taking Graphs to the Next Level with Artificial Intelligence and Machine Learning - April 22-27, 2018
Text Analytics 17
The 22nd Annual Enterprise Data World (EDW) Conference hosted by DATAVERSITY® is recognized as the most comprehensive educational conference on data management in the world. Join hundreds of data professionals from around the globe to attend this unique conference. Your transformation to data-driven business starts here!
Franz CEO Jans Aasman will be presenting "Taking Graphs to the Next Level with Artificial Intelligence and Machine Learning".
Graphs and Knowledge Management have gained significant visibility with the rebirth of artificial intelligence and emergence of cognitive computing. By combining artificial intelligence, big data, graph databases, and dynamic visualizations, we will discuss deploying Graph based AI applications as a means to help predict future events across numerous types of industries.
Knowledge creation via AI and Graphs stems from the capability to combine the probability space (i.e. statistical inference on a user’s data) with a knowledge base of comprehensive industry terminology systems. AI using Graphs are remarkable not just because of the possibilities they engender, but also because of their practicality. The confluence of knowledge via machine learning, visual querying, graph databases, and big data not only displays links between objects, but also quantifies the probability of their occurrence. We believe this approach will be transformative across numerous business verticals.
During the presentation we will describe the Graph based AI concepts that also incorporate Hadoop, along with analytics via R, SPARK ML and other AI techniques for practical Enterprise predictive analytics use cases.
For additional information, see here

AllegroGraph 6.3 - Now Available
franz logo

New Features Include:

  • Defining your own magic properties - AllegroGraph lets you define your own Magic Properties. The Defining Magic Properties Tutorial describes how to do this and provides numerous simple examples.
  • Improvements and new features in AGWebView, including the ability to add data by pasting in a text area, new report dialogs which detail storage usage and other things, a new index management page. See the 6.3.0 programmer notes for details of the changes to AGWebView.
  • Support for XQuery and XPath math functions.
  • CORS support: CORS (Cross-Origin Resource Sharing), if enabled, allows scripts run on a web page from one server to make HTTP requests to the (different) server where AllegroGraph is running.
For additional information, see here

Gruff v7.2 - Now Available
gruff screen shot
New Features Include:
  • The new command "Global Options | Show Non-Default Option Values" lists option values that you have changed from their defaults. That may be useful for finding options that you might like to revert to their default values without reverting all options. (This list will also be included in any bug report that Gruff generates.)
  • When using "View | Go Back" and "View | Go Forward" in the graph view, if "Visual Graph Options | Layout Options | Animate Layouts" is enabled then the nodes will slide smoothly from one history state to the next.
  • Path-finding will now display paths that contain literals even when "Global Options | Miscellaneous | Treat Literals as Objects" is off (as it is by default).
  • If you turn off the new option "Visual Graph Options | Inclusion Options | Include Literals of All Languages", then commands on the Link menu will add literal nodes to the visual graph only when they have no language or their language tag is the "Global Options | Miscellaneous | Preferred Language".
  • The option "Global Options | Node Label Predicates | Label Property Language" has become the more general "Global Options | Miscellaneous | Preferred Language". It also has a new "Other" choice at the bottom for specifying any language, rather than being limited to the several choices in the list. (And the more obscure "Global Options | Localization Language" has been moved into the Miscellaneous child menu.)
  • The Global Options menu has two new child menus called "Node Label Type" and "Font". Like the "Timeouts" child menu that was already there, these new menus contain options that appear elsewhere on the menu bar in scattered places, and are simply grouped in a different way on these new menus to make it easier to find all of the options of their kind.
  • The keyboard shortcut for doing a tree layout is now T with no shift key, to correspond to the other layout commands that also use no shift key. This means that the keyboard shortcut for going to the table view is now B instead of T.
  • The new option "File | Load Triples | Base URI for RDF/XML and Turtle" allows you to specify the base URI that will be passed to AllegroGraph when using the commands for loading triples from RDF/XML files or turtle files.
  • Changes to the time chart: (1) Fixed: The time chart could break in certain cases while adjusting the time bar range or resizing Gruff while the time chart is present. (2) The time chart has been improved stylistically, such as by placing each date label in the middle of its time range rather than at the beginning of it. (3) The new command "View | Optional Graph View Panes | Show Time Chart" (with its keyboard shortcut) allows more quickly toggling the time chart on and off than by clicking the button for it on the time bar.
  • The new option "Visual Graph Options | Finding Paths Between Nodes | Maximum Paths to Find" causes path-finding to return if it has found that many paths, to avoid wasting time finding additional paths that you would not display anyway. This option will not have an effect until AllegroGraph 6.3.1 is out and Gruff is built on it.

For additional information, see the Gruff Documentation

Dataconomy article - Triple Attributes: A New Way to Protect the Most Sensitive Information
Dataconomy logo
Semantic Graph Databases are now common in many industries, including life sciences, healthcare, the financial industry and in government and intelligence agencies. Graphs are particularly valuable in these sectors because of the complex nature of the data and need for powerful, yet flexible data analytics.
Attributes, user attributes and static filters are a new mechanism for graph databases to protect sensitive information. This combination provides the right amount of power and flexibility to address high-security use cases, such as: HIPAA access controls, privacy rules for banks, security models for policing, intelligence and the government. In addition, this set of methods is far easier to use, provides more expressiveness than security methods in relational databases and doesn’t suffer from performance degradations.
To read the full article, see here

Datanami article - Why Enterprise Knowledge Graphs Need Semantics
Datanami logo
The Enterprise Knowledge Graph concept strikes at the core of what every data-driven organization is trying to do: translate data assets into a competitive advantage unique to those assets and the company itself.
By effectively connecting enterprise-wide data—both internal and external—into a sole repository reusable for a variety of use cases across an organization, Enterprise Knowledge Graphs are the single most effective mechanism for accomplishing this objective. The proliferation of use cases spanning Silicon Valley’s finest proves this point as well as the business value of this methodology.
To read the full article, see here

Franz Inc. named to The Silicon Review 50 Fastest Growing Tech Companies 2017
Big Data logo


Franz Inc., an early innovator in Artificial Intelligence and leading supplier of Semantic Graph Database technology - AllegroGraph, announced that it has been named to The Silicon Review 50 Fastest Growing Tech Companies 2017 - Delivering Scalable Knowledge Graph solutions Franz Inc...


Big Data 50 - Companies Driving Innovation in 2017 - Franz Inc.
Big Data logo
Used by Fortune 500 companies that span healthcare, intelligence agencies, life sciences, telecommunications, and research organizations, Franz provides AllegroGraph, a high-performance and transactional semantic graph database, and Allegro CL, a Lisp programming environment to create complex applications for solving real-world problems.
AllegroGraph is a database technology that enables businesses to extract sophisticated decision insights and predictive analytics from highly complex, distributed data that cannot be uncovered with conventional databases. Unlike traditional relational databases or other NoSQL databases, AllegroGraph employs semantic graph technologies that process data with contextual and conceptual intelligence. AllegroGraph is able run queries of unprecedented complexity to support predictive analytics that help organizations make more informed, real-time decisions.
To read the full article, see here

Follow us on Google Plus, Twitter, LinkedIn, and YouTube 

Thursday, November 2, 2017

AllegroGraph News - November 2017

In this issue

AllegroGraph 6.3 - Now Available
franz logo

New Features Include:

  • Defining your own magic properties - AllegroGraph lets you define your own Magic Properties. The Defining Magic Properties Tutorial describes how to do this and provides numerous simple examples.
  • Improvements and new features in AGWebView, including the ability to add data by pasting in a text area, new report dialogs which detail storage usage and other things, a new index management page. See the 6.3.0 programmer notes for details of the changes to AGWebView.
  • Support for XQuery and XPath math functions.
  • CORS support: CORS (Cross-Origin Resource Sharing), if enabled, allows scripts run on a web page from one server to make HTTP requests to the (different) server where AllegroGraph is running.
For additional information, see here

Gruff v7.2 - Available November 10th
gruff screen shot
New Features Include:
  • The new command "Global Options | Show Non-Default Option Values" lists option values that you have changed from their defaults. That may be useful for finding options that you might like to revert to their default values without reverting all options. (This list will also be included in any bug report that Gruff generates.)
  • When using "View | Go Back" and "View | Go Forward" in the graph view, if "Visual Graph Options | Layout Options | Animate Layouts" is enabled then the nodes will slide smoothly from one history state to the next.
  • Path-finding will now display paths that contain literals even when "Global Options | Miscellaneous | Treat Literals as Objects" is off (as it is by default).
  • If you turn off the new option "Visual Graph Options | Inclusion Options | Include Literals of All Languages", then commands on the Link menu will add literal nodes to the visual graph only when they have no language or their language tag is the "Global Options | Miscellaneous | Preferred Language".
  • The option "Global Options | Node Label Predicates | Label Property Language" has become the more general "Global Options | Miscellaneous | Preferred Language". It also has a new "Other" choice at the bottom for specifying any language, rather than being limited to the several choices in the list. (And the more obscure "Global Options | Localization Language" has been moved into the Miscellaneous child menu.)
  • The Global Options menu has two new child menus called "Node Label Type" and "Font". Like the "Timeouts" child menu that was already there, these new menus contain options that appear elsewhere on the menu bar in scattered places, and are simply grouped in a different way on these new menus to make it easier to find all of the options of their kind.
  • The keyboard shortcut for doing a tree layout is now T with no shift key, to correspond to the other layout commands that also use no shift key. This means that the keyboard shortcut for going to the table view is now B instead of T.
  • The new option "File | Load Triples | Base URI for RDF/XML and Turtle" allows you to specify the base URI that will be passed to AllegroGraph when using the commands for loading triples from RDF/XML files or turtle files.
  • Changes to the time chart: (1) Fixed: The time chart could break in certain cases while adjusting the time bar range or resizing Gruff while the time chart is present. (2) The time chart has been improved sylistically, such as by placing each date label in the middle of its time range rather than at the beginning of it. (3) The new command "View | Optional Graph View Panes | Show Time Chart" (with its keyboard shortcut) allows more quickly toggling the time chart on and off than by clicking the button for it on the time bar.
  • The new option "Visual Graph Options | Finding Paths Between Nodes | Maximum Paths to Find" causes path-finding to return if it has found that many paths, to avoid wasting time finding additional paths that you would not display anyway. This option will not have an effect until AllegroGraph 6.3.1 is out and Gruff is built on it.

For additional information, see the Gruff Documentation
Available November 10th. Contact info@franz.com to test an early release.

Dataconomy article - Triple Attributes: A New Way to Protect the Most Sensitive Information
Dataconomy logo
Semantic Graph Databases are now common in many industries, including life sciences, healthcare, the financial industry and in government and intelligence agencies. Graphs are particularly valuable in these sectors because of the complex nature of the data and need for powerful, yet flexible data analytics.
Attributes, user attributes and static filters are a new mechanism for graph databases to protect sensitive information. This combination provides the right amount of power and flexibility to address high-security use cases, such as: HIPAA access controls, privacy rules for banks, security models for policing, intelligence and the government. In addition, this set of methods is far easier to use, provides more expressiveness than security methods in relational databases and doesn’t suffer from performance degradations.
To read the full article, see here

Datanami article - Why Enterprise Knowledge Graphs Need Semantics
Datanami logo
The Enterprise Knowledge Graph concept strikes at the core of what every data-driven organization is trying to do: translate data assets into a competitive advantage unique to those assets and the company itself.
By effectively connecting enterprise-wide data—both internal and external—into a sole repository reusable for a variety of use cases across an organization, Enterprise Knowledge Graphs are the single most effective mechanism for accomplishing this objective. The proliferation of use cases spanning Silicon Valley’s finest proves this point as well as the business value of this methodology.
To read the full article, see here

Big Data 50 - Companies Driving Innovation in 2017 - Franz Inc.
Big Data logo
Used by Fortune 500 companies that span healthcare, intelligence agencies, life sciences, telecommunications, and research organizations, Franz provides AllegroGraph, a high-performance and transactional semantic graph database, and Allegro CL, a Lisp programming environment to create complex applications for solving real-world problems.
AllegroGraph is a database technology that enables businesses to extract sophisticated decision insights and predictive analytics from highly complex, distributed data that cannot be uncovered with conventional databases. Unlike traditional relational databases or other NoSQL databases, AllegroGraph employs semantic graph technologies that process data with contextual and conceptual intelligence. AllegroGraph is able run queries of unprecedented complexity to support predictive analytics that help organizations make more informed, real-time decisions.
To read the full article, see here

The Open Data Science Conference (ODSC West), November 2-4, Hyatt Regency San Francisco Airport
ODSC logo
ODSC – Open Data Science Conference – is essential for anyone who wants to connect to the data science community and contribute to the open source applications they use everyday. Our goal is to bring together the global data science community to help foster the exchange of innovative ideas and encourage the growth of open source software.
Join us at ODSC West - Nov 2-4. https://odsc.com/california

The Text Analytics Forum 2017 - Washington DC, November 8-9
Text Analytics 17
Text Analytics is a platform technology that adds depth and intelligence to any organization's ability to utilize that most under-utilized resource - text. For many years the exponential growth of information has been experienced as a problem - information overload. However, with a new generation of text analytics tools and techniques, massive amounts of information are becoming part of the solution for an incredibly wide range of applications, from search that works to social media-fueled insights about customers and competitors to new flexible approaches to KM, new solutions to fake news, and more. The inaugural theme for Text Analytics Forum, Go Deeper, invites all who deal with text to take a deep dive into this powerful set of techniques.
For additional information, see here

Enterprise Data World - Taking Graphs to the Next Level with Artificial Intelligence and Machine Learning - April 22-27, 2018
Text Analytics 17
The 22nd Annual Enterprise Data World (EDW) Conference hosted by DATAVERSITY® is recognized as the most comprehensive educational conference on data management in the world. Join hundreds of data professionals from around the globe to attend this unique conference. Your transformation to data-driven business starts here!
Franz CEO Jans Aasman will be presenting "Taking Graphs to the Next Level with Artificial Intelligence and Machine Learning".
Graphs and Knowledge Management have gained significant visibility with the rebirth of artificial intelligence and emergence of cognitive computing. By combining artificial intelligence, big data, graph databases, and dynamic visualizations, we will discuss deploying Graph based AI applications as a means to help predict future events across numerous types of industries.
Knowledge creation via AI and Graphs stems from the capability to combine the probability space (i.e. statistical inference on a user’s data) with a knowledge base of comprehensive industry terminology systems. AI using Graphs are remarkable not just because of the possibilities they engender, but also because of their practicality. The confluence of knowledge via machine learning, visual querying, graph databases, and big data not only displays links between objects, but also quantifies the probability of their occurrence. We believe this approach will be transformative across numerous business verticals.
During the presentation we will describe the Graph based AI concepts that also incorporate Hadoop, along with analytics via R, SPARK ML and other AI techniques for practical Enterprise predictive analytics use cases.
For additional information, see here

Franz Inc. named to the DBTA 100 - The Companies That Matter Most in Data
DBTA 100logo
Franz Inc., an early innovator in Artificial Intelligence and leading supplier of Semantic Graph Database technology, announced it has been named to the Database Trends and Applications (DBTA) 100 - 'The Companies That Matter Most in Data'. The world of data management is constantly changing. The DBTA 100 recognizes vendors who are evolving with the times and leading the charge to address new opportunities and requirements. Embracing the old and new, well-established and cutting edge, this fifth annual DBTA 100 list spotlights the companies that are dealing with evolving market demands through innovation in software, services, and hardware. The list includes long-established IT companies and newer upstarts anxious to shake up the data management space. Each year, the DBTA 100 presents "View from the Top" articles by company executives explaining how their organizations are uniquely addressing the data challenges of today and tomorrow...
See here to read the full release