Tag Archives: Rules Engine

AI, Business, Technology

Applying Artificial Intelligence & Machine Learning to Data Warehousing

Leave a comment
Protecting the Data Warehouse with Artificial Intelligence

Teleran is a middleware company who’s software monitors and governs OLAP activity between the Data Warehouse and Business Intelligence tools, like Business Objects and Cognos.   Teleran’s suite of tools encompass a comprehensive analytical and monitoring solution called iSight.  In addition, Teleran has a product that leverages artificial intelligence and machine learning to impose real-time query and data access controls.  Architecture  also allows for Teleran’s agent not to be on the same host as the database, for additional security and prevention of utilizing resources from the database host.

Key Features of iGuard:
  • Policy engine prevents “bad” queries before reaching database
  • Patented rule engine resides in-memory to evaluate queries at database protocol layer on TCP/IP network
  • Patented rule engine prevents inappropriate or long-running queries from reaching the data
70 Customizable Policy Templates
SQL Query Policies
  • Create policies using policy templates based on SQL Syntax:
    • Require JOIN to Security Table
    • Column Combination Restriction –  Ex. Prevents combining customer name and social security #
    • Table JOIN restriction –  Ex. Prevents joining two different tables in same query
    • Equi-literal Compare requirement – Tightly Constrains Query Ex. Prevents hunting for sensitive data by requiring ‘=‘ condition
    • DDL/DCL restrictions (Create, Alter, Drop, Grant)
    • DQL/DML restrictions (Select, Insert, Update, Delete)
Data Access Policies

Blocks access to sensitive database objects

  • By user or user groups and time of day (shift) (e.g. ETL)
    • Schemas
    • Tables/Views
    • Columns
    • Rows
    • Stored Procs/Functions
    • Packages (Oracle)
Connection Policies

Blocks connections to the database

  • White list or black list by
    • DB User Logins
    • OS User Logins
    • Applications (BI, Query Apps)
    • IP addresses
Rule Templates Contain Customizable Messages

Each of the “Policy Templates”  has the ability to send the user querying the database a customized message based on the defined policy. The message back to the user from Teleran should be seamless to the application user’s experience.

iGuard Rules Messaging
iGuard Rules Messaging

 

Machine Learning: Curbing Inappropriate, or Long Running Queries

iGuard has the ability to analyze all of the historical SQL passed through to the Data Warehouse, and suggest new, customized policies to cancel queries with certain SQL characteristics.   The Teleran administrator sets parameters such as rows or bytes returned, and then runs the induction process.  New rules will be suggested which exceed these defined parameters.  The induction engine is “smart” enough to look at the repository of queries holistically and not make determinations based on a single query.

Finally, here is a high level overview of the implementation architecture of iGuard.  For sales or pre-sales technical questions, please contact www.teleran.com

Teleran Logical Architecture
Teleran Logical Architecture

 

Currently Featured Clients
Teleran Featured Clients
Teleran Featured Clients

 

Business, Development, Economy, Entertainment, Media, Technology

Twitter Trolls caused Salesforce to Walk Away from Deal? Google reCAPTCHA to the Rescue!?

Leave a comment

According to CNBC’s “Mad Money” host Jim Cramer, Salesforce was turned off by a more fundamental problem that’s been hurting Twitter for years: trolls.

“What’s happened is, a lot of the bidders are looking at people with lots of followers and seeing the hatred,” Cramer said on CNBC’s “Squawk on the Street,” citing a recent conversation with Benioff. “I know that the haters reduce the value of the company…I know that Salesforce was very concerned about this notion.”

…Twitter’s troll problem isn’t anything new if you’ve been following the company for a while.”

Source: Twitter trolls caused Salesforce to walk away from deal – Business Insider

Anyone with a few neurons will recognize that bots on Twitter are a huge turnoff in some cases.  I like periodic famous quotes as much as the next person, but it seems like bots have invaded Twitter for a long time, and becomes a detractor to using the platform.  The solution in fact is quite easy, reCAPTCHA.  a web application that determines if the user is a human and not a robot.  Twitter users should be required to use an integrated reCAPTCHA Twitter DM, and/or as a “pinned”reCAPTCHA tweet that sticks to the top of your feed,  once a calendar week, and go through the “I’m not a robot” quick and easy process.

Additionally, an AI rules engine may identify particular patterns of Bot activity, flag it, and force the user to go through the Human validation process within 24 hours.  If users try to ‘get around’ the Bot\Human identification process,  maybe by tweaking their tweets, Google may employ AI machine learning algorithms to feed the “Bot” AI rules engine patterns.

Every Twitter user identified as “Human” would have the picture of the “Vitruvian Man” by  Leonardo da Vinci miniaturized, and placed next to the “Verified Account” check mark.  Maybe there’s a fig leaf too.

In addition, the user MAY declare it IS a bot, and there are certainly valid reasons to utilize bots.  Instead of the “Man” icon, Twitter may allow users to pick the bot icon, including the character from the TV show “Futurama”, Bender miniaturized.  Twitter could collect additional information on Bots for enhanced user experience, e.g. categories and subcategories

reCAPTCHA is owned by Google, so maybe, in some far out distant universe, a Doppelgänger Google would buy Twitter, and either phase out or integrate G+ with Twitter.

If trolls/bots are such a huge issue, why hasn’t Twitter addressed it?  What is Google using to deal with the issue?

The prescribed method seems too easy and cheap to implement, so I must be missing something.  Politics maybe?  Twitter calling upon a rival, Google (G+) to help craft a solution?

Business, Economy, Entertainment, Finance, Legal, Media, Mobility, Music, Technology, Work

Microsoft Flow – Platform Review

Leave a comment

It looks like Microsoft created a generic workflow platform, product independent.

Microsoft has software solutions, like MS Outlook with an [email] rules engine built into Outlook.  SharePoint has a workflow solution within the Sharepoint Platform, typically governing the content flowing through it’s system.

Microsoft Flow is a different animal.  It seems like Microsoft has built a ‘generic’ rules engine for processing almost any event.  The Flow product:

  1. Start using the product from one of two areas:  a) “My Flows” where I may view existing and create new [work]flows. b) “Activity”, that shows “Notifications” and “Failures”
  2. Select “My Flows”, and the user may “Create [a workflow] from Blank”,  or “Browse Templates”.  MSFT existing set of templates were created by Microsoft, and also by a 3rd party implying a marketplace.
  3. Select “Create from Blank” and the user has a single drop down list of events, a culmination events across Internet products. There is an implication there could be any product, and event “made compatible” with MSFT Flows.
    1. The drop down list of events has a format of “Product – Event”.  As the list of products and events grow, we should see at least two separate drop down lists, one for products, and a sub list for the product specific events.
    2. Several Example Events Include:
      1. “Dropbox – When a file is created”
      2. “Facebook – When there is a new post to my timeline”
      3. “Project Online – When a new task is created”
      4. “RSS – When a feed item is published”
      5. “Salesforce – When an object is created”
    3. The list of products as well as there events may need a business analyst to rationalize the use cases.
  4. Once an Event is selected, event specific details may be required, e.g. Twitter account details, or OneDrive “watch” folder
  5. Next, a Condition may be added to this [work]flow,  and may be specific to the Event type, e.g. OneDrive File Type properties [contains] XYZ value.  There is also an “advanced mode” using a conditional scripting language.
  6. There is “IF YES” and “IF NO” logic, which then allows the user to select one [or more] actions to perform
    1. Several Action Examples Include:
      1. “Excel – Insert Rows”
      2. “FTP – Create File”
      3. “Google Drive – List files in folder”
      4. “Mail – Send email”
      5. “Push Notification – Send a push notification”
    2. Again, it seems like an eclectic bunch of Products, Actions, and Events strung together to have a system to POC.
  7. The Templates list, predefined set of workflows that may be of interest to anyone who does not want to start from scratch.   The UI provides several ways to filter, list, and search through templates.

Applicable to everyday life, from an individual home user, small business, to the enterprise.  At this stage the product seems in Beta at best, or more accurately, just after clickable prototype.  I ran into several errors trying to go through basic use cases, i.e. adding rules.

Despite the “Preview” launch, Microsoft has showed us the power in [work]flow processing regardless of the service platform provider, e.g.  Box, DropBox, Facebook, GitHub, Instagram, Salesforce, Twitter, Google, MailChimp, …

Microsoft may be the glue to combine service providers who may / expose their services to MSFT Flow functionality.

Create from Blank - Select Condition
Create from Blank – Select Condition

 

Create Rule from Template
Create Rule from Template
Create from Blank Rule Building UI
Create from Blank Rule Building UI

 

Update June 28th, 2016:

Opportunities for Event, Condition, Action Rules

  • Transcoding [cloud] Services
  • [IBM Watson] Cognitive APIs
    • e.g. Language:Translation; E.g.2. Visual Recognition;
  • WordPress – Create a Post
    • New text file dropped in specific folder on Box, DropBox, etc. being ‘monitored’ by MSFT flow [?] Additional code required by user for ‘polling’ capabilities
    • OR new text file attached, and emailed to specific email account folder ‘watched’ by MSFT Flow.
    • Event triggers – Automatic read of new text file
      • stylizing may occur if HTML coding used
    • Action – Post to a Blog
  • ‘ANY’ Event occurs, a custom message is sent using Skype for a single or group of Skype accounts;
    • On several ‘eligible’ events, such as “File Creation” into Box,  the file (or file shared URL) may be sent to the Skype account.
  • ‘ANY’ Event occurs, a custom mobile text message is sent to a single or group of phone numbers.
  • Event occurs for “File Creation” e.g. into Box; after passing a “Condition”, actions occur:
    • IBM Watson Cognitive API, Text to Speech, occurs, and the product of the action is placed in the same Box folder.
  • Action: Using Microsoft Edge (powered by MSN), in the “My news feed” tab, enable action to publish “Cards”, such as app notifications

Challenges \ Opportunities \ Unknowns

  • 3rd party companies existing, published [cloud; web service] APIs may not even need any modification to integrate with Microsoft Flow; however, business approval may be required to use the API in this manner,
  • It is unclear re: Flow Templates need to be created by the product owner, e.g. Telestream, or knowledgeable third party, following the Android, iOS, and/or MSFT Mobile Apps model.
  • It is unclear if the MSFT Flow app may be licensed individually in the cloud, within the 365 cloud suite, or offered for Home and\or Business?
Advertising, Business, Development, Economy, Education, Entertainment, Fashion, Finance, Fun, Law, Retail, Science, Technology

The Race Is On to Control Artificial Intelligence, and Tech’s Future

Leave a comment

Amazon, Google, IBM and Microsoft are using high salaries and games pitting humans against computers to try to claim the standard on which all companies will build their A.I. technology.

In this fight — no doubt in its early stages — the big tech companies are engaged in tit-for-tat publicity stunts, circling the same start-ups that could provide the technology pieces they are missing and, perhaps most important, trying to hire the same brains.

For years, tech companies have used man-versus-machine competitions to show they are making progress on A.I. In 1997, an IBM computer beat the chess champion Garry Kasparov. Five years ago, IBM went even further when its Watson system won a three-day match on the television trivia show “Jeopardy!” Today, Watson is the centerpiece of IBM’s A.I. efforts.

Today, only about 1 percent of all software apps have A.I. features, IDC estimates. By 2018, IDC predicts, at least 50 percent of developers will include A.I. features in what they create.

Source: The Race Is On to Control Artificial Intelligence, and Tech’s Future – The New York Times

The next “tit-for-tat” publicity stunt should most definitely be a battle with robots, exactly like BattleBots, except…

  1. Use A.I. to consume vast amounts of video footage from previous bot battles, while identifying key elements of bot design that gave a bot the ‘upper hand’.  From a human cognition perspective, this exercise may be subjective. The BattleBot scoring process can play a factor in 1) conceiving designs, and 2) defining ‘rules’ of engagement.
  2. Use A.I. to produce BattleBot designs for humans to assemble.
  3. Autonomous battles, bot on bot, based on Artificial Intelligence battle ‘rules’ acquired from the input and analysis of video footage.
Business, Science, Science Fiction, Technology

Editorial: 4D printed objects that make themselves

Leave a comment

BBC News – TED 2013: 4D printed objects make themselves.

A simple rules engine that has the ability to create itself, is a slippery slope, perhaps, one of dramatic proportions such as “4D” printing. The concepts are clear from the article, as well as the experiments at MIT.

The value of combining a rules engine to printed or created object, that can transform itself, or evolve has vast applications, such as the simple scope, as defined in the article, to the more dramatic concepts we can only imagine in what was once Science Fiction.  The applications vary from the horrific to the wondrous.  I will leave it to the readers imagination.  Although there are significant revenue opportunities in 4D printed objects, objects that make themselves, there may be a question of ethics, and governance, now that the genie is out of the bottle.

Business, Science, Technology

Artificial Intelligence: Tuning with a Content Index And Predictive Models

Leave a comment

As I was reading an All Things Digital article, Artificial-Intelligence Professor Makes a Search App to Outsmart Siri, there was a statement that made:

“We memorize the dictionary to read the Library of Congress,” he said. “Siri is trying to memorize the Library of Congress.”

 

A tool more commonly used in the past, in books, at the end of a book, an index of where the words appeared in the book was noted with page numbers.  Classic rules engines is ‘data in a black box’, searchable within the context they appear. The more put into the black box, users can search on ‘rules’ or content, and in precedence, an action occurs, or the content that is searched appears.  If there are cross-references with an associated category or tag with ‘each line of data’ or ‘rule’ that will enable the Artificial Intelligence engine to be more efficient.  Therefore the correlations of ‘data to other data’ with similar or like tags enables an Artificial Intelligence will be more intelligent.  In theory, categorized or tagged content indexed to references of the data points should fine tune the engine.

An addition theory, allows for predictive models to produce refined searches, or rules.  You can make a predictive model, where the intelligence of the user actually refines the engine. The user can ask a question, and as they refine their question, a predictive model,  may allow for refined user output.  If a user is allowed to participate and tag data search output, the search output could be more granular, like a refined Business Intelligence drill down.  The output of a search, for example, can contain a title, brief summary, and tags that can be added or removed (by the user), which allows for a more robust search, and predictive model; however, you are relying on the user to a) not be malicious, and b) have understanding of what information he is search for within the data.  If web crawlers, or if the webmaster submits URLs with tags, the meta data tags of the page, the black box or Artificial Intelligence rules engine will, if properly submitted, or indexed, correlate the data.  To most people, this is AI or Search Engine 101.  Some people cheat, and add pages with false meta data tags because they want their site to appear in a higher order, or precedence and they may make more revenue with advertising dollars.

There are multiple ways around trying to cheat an Artificial Intelligence Content Index:

  • Hit Ratio: People searching on the same question over and over increase the ‘score’ ratio, thus pushing the false results downward on the list, or removing them entirely.
  • Enlist ‘quality’ users, who are known quantities, such as like Twitter ‘certifies’ certain users.  You may apply for ‘relatively’ unbiased, certification status, such as people who have reputations and certifications in the field, are qualified to ‘enhance’ tags, and improve upon your result outputs. e.g Professors, Statisticians,
  • Enlist users who will actually derive revenue, if their ‘hit ratio’ score delta increases exponentially some N number.  These tags are classified as unverified, however, the people are monetarily motivated to increase peoples’ probably of success to find what people are looking for when other users search the tags become qualified as the results of the tags attract users to their content.  If they are using, let’s say, a browser, which the search engine company owns, such as Chrome, a little plug in can appear and say, was this what you were looking to find, yes or no.