• Home
  • About Us
  • Contact Us
  • Privacy Policy
  • Special Offers
Business Intelligence Info
  • Business Intelligence
    • BI News and Info
    • Big Data
    • Mobile and Cloud
    • Self-Service BI
  • CRM
    • CRM News and Info
    • InfusionSoft
    • Microsoft Dynamics CRM
    • NetSuite
    • OnContact
    • Salesforce
    • Workbooks
  • Data Mining
    • Pentaho
    • Sisense
    • Tableau
    • TIBCO Spotfire
  • Data Warehousing
    • DWH News and Info
    • IBM DB2
    • Microsoft SQL Server
    • Oracle
    • Teradata
  • Predictive Analytics
    • FICO
    • KNIME
    • Mathematica
    • Matlab
    • Minitab
    • RapidMiner
    • Revolution
    • SAP
    • SAS/SPSS
  • Humor

AI on Demand: Data Science in Operations

March 3, 2019   TIBCO Spotfire

Artificial intelligence (AI) is right here, right now—and it’s changing our lives. The ever-present need for business optimization, combined with a long history of applied statistics, explosive growth in available data and recent advances in cloud computing has accelerated innovation and business transformation.

However, creating and implementing AI systems is tricky – many things to get right, many technology options and many human and business considerations. This article covers the major functions and issues of AI at a high level. The accompanying webinar and series of workshops show how to run AI systems at scale, and how to enable AI-driven applications across a variety of functions and business areas. The workshops feature TIBCO Connected Intelligence technology, which embodies all the major functions of AI – at scale in a single platform.

AI technologies

In recent years we’ve been teaching machines ever-more human tasks. Speech recognition and in-home agents like Amazon’s Alexa. Image recognition like Clear identifying and checking travelers in at the airport with fingerprint and eye recognition. Natural language processing and chat-bots that help customers troubleshoot their cable service. These AI techniques are firmly rooted in some areas, but still difficult to get AI to function on-demand and get Data Science into operations. “The future is here, but it’s not evenly distributed” as William GIbson says.

Some AI-driven systems we take for granted as part of daily life. For example,  recommendation systems analyze at our current behavior and purchase history and make personalized suggestions — Amazon for online purchases, Netflix for movie recommendations, and Spotify for music playlists.

More than this, the many real-life business applications that I see with TIBCO customers, is a constant reminder of the value driven by AI and Data Science. AI helps all industries perform tasks otherwise not possible — such as managing financial risk, spotting fraudulent transactions, detecting and treating diseases, optimizing energy production, detecting anomalies in the manufacturing of computer chips, forecasting demand, engaging customers and protecting the environment.

So, where did all this AI stuff come from all of a sudden?

Well, it turns out that the core ideas of AI are based on technologies built over years of mathematical statistics and computer science, that can now be run quickly and at scale. AI is algorithms — trained on historical data and managed in computer software pipelines, generating predictions that are actioned by business rules on event streams.  

Machine Learning and Data Science

The poster child for AI in recent years is machine learning (ML), especially the emergence of deep learning. Machine learning models are trained on historical data and predict from new observations. Broadly speaking, supervised learning models predict a target variable from other variables while unsupervised learning models identify patterns in data without focusing on a target. Classification models classify new observations into various categories like whether a credit card transaction is fraudulent or not, or if regression models can identify anomalies in IoT systems such as oil and gas production.

Extreme value is generated, and businesses are transformed, when ML models and AI apps are deployed into operations — making predictions on the data that flow through a business. That state of AI on Demand with Data Science Models in Operations is the hallmark of a successful AI business system.

While AI systems are generally developed to drive innovation and business transformation, we note that there is also the potential for unintended consequence and even a dark side as described by the tehno-sociologist Zynep Tufekci in her TED Talk, “building a dystopia to make people click on ads”. Indeed, with concepts such as hyper-personalization,  people now getting the news that they want to see, and some studies show falsehoods spread six times faster than truisms. As a practical matter, we are seeing regulations and ethical oversights driving “model fairness” – preventing discrimination against age, sex, race, communities; via enforcing data and models that don’t discriminate.

TIBCO Connected Intelligence — AI on Demand: Data Science in Operations

In TIBCO’s “AI on Demand with Data Science Models in Operations” series, we highlight some of these AI success areas and showcase the underlying data science and application creation. This 10-city workshop tour features signature software demonstrations in recommenders and suggestion engines, customer engagement, dynamic pricing, risk management, and energy production surveillance. These demonstrations are based on real-world TIBCO deployments, driving extreme value for TIBCO customers across many industry sectors and functions.

We’ll be showing the new TIBCO Spotfire X and TIBCO Data Science products, and you’ll see demonstrations of how to detect anomalies in data with lots of dimensions, how to handle extremely wide datasets, how visual analytics are auto-suggested from the data, how streaming and static data sources interplay in data discovery, and how to build models and deploy them as a service.

The series features data science design patterns that we are publishing to the TIBCO Community site along the way.

Watch the webinar today to learn how you can implement AI driven by data science in your own organization.

Let’s block ads! (Why?)

The TIBCO Blog

data, Demand, operations, Science
  • Recent Posts

    • 5 CRM Marketing Tips to Use as Resolutions for 2021
    • Sidney Poitier To Get A School Named After Him
    • Using Power Automate to Automatically Move Your Email Attachments to SharePoint
    • Why it’s time for fintechs and FIs to jump on the open banking bandwagon (VB Live)
    • Integrating a function with integration limits also dependent on a variable
  • Categories

  • Archives

    • January 2021
    • December 2020
    • November 2020
    • October 2020
    • September 2020
    • August 2020
    • July 2020
    • June 2020
    • May 2020
    • April 2020
    • March 2020
    • February 2020
    • January 2020
    • December 2019
    • November 2019
    • October 2019
    • September 2019
    • August 2019
    • July 2019
    • June 2019
    • May 2019
    • April 2019
    • March 2019
    • February 2019
    • January 2019
    • December 2018
    • November 2018
    • October 2018
    • September 2018
    • August 2018
    • July 2018
    • June 2018
    • May 2018
    • April 2018
    • March 2018
    • February 2018
    • January 2018
    • December 2017
    • November 2017
    • October 2017
    • September 2017
    • August 2017
    • July 2017
    • June 2017
    • May 2017
    • April 2017
    • March 2017
    • February 2017
    • January 2017
    • December 2016
    • November 2016
    • October 2016
    • September 2016
    • August 2016
    • July 2016
    • June 2016
    • May 2016
    • April 2016
    • March 2016
    • February 2016
    • January 2016
    • December 2015
    • November 2015
    • October 2015
    • September 2015
    • August 2015
    • July 2015
    • June 2015
    • May 2015
    • April 2015
    • March 2015
    • February 2015
    • January 2015
    • December 2014
    • November 2014
© 2021 Business Intelligence Info
Power BI Training | G Com Solutions Limited