Entity matching in Customer 360 is the task of determining if multiple records represent the same real world entity. Entities are typically people, organizations, locations, and events represented as attributed nodes in a graph, though they can also be represented as records in relational data. While probabilistic matching engines and artificial neural network models exist for this task, explaining entity matching has received less attention. In this demo, we present our Explainable Entity Matching (xEM) system and discuss the different AI/ML considerations that went into its implementation.

Every company has got some automation -- if not artificial intelligence (AI) -- initiatives going on. Assess where you are in the progression and where you might want to go. Below is a list of critical use-cases on a road map to AI adoption, along with the complexity and advantages gained. Two exciting use cases for AI in supporting customers are chatbots and sentiment analysis. Remember when there were first just numbered options spoken in a mechanical voice that needed to be navigated?

Transcription and information extraction, which converts all unstructured data into machine-readable formats, whether it's call centers, calls, texts or onboarding documentation Natural language processing Knowledge graphs, which allow you to put your data in a graph topology with a machine reasoning inference, are all new capabilities that enable a lot of machine learning use cases. You'll see how we do this for money laundering.

Prefer to watch – here is my event video … (if the video doesn't' show up – check here) Here is the 1 slide condensation (if the slide doesn't show up, check here): Event Report - Dreamforce 2018 - Where is the Innovation from Holger Mueller Want to read on? Here you go: Salesforce and Apple partner. At first glance, enterprises love it when market leaders' partner, especially when they are joint customers. With Salesforce committing to build iOS specific apps, taking advantage of iPhone features, moving closer to Swift – is a big favor to Apple. The concern for CIOs is – Salesforce is creating two classes of mobile users.

Salesforce's big idea is one that you've heard of before from other enterprise software vendors--a 360 degree view of the customer--with different lens. The big question will come down to executing Salesforce's effort, dubbed Customer 360. At Dreamforce, Salesforce's developer and customer powwow, the company will outline Customer 360, which includes the following: Also: Here's why the public cloud is growing rapidly TechRepublic Co-CEO Marc Benioff and CTO Parker Harris in their Dreamforce keynote outlined Customer 360. Benioff reiterated his customer-first mantra and talked about how companies have to be about their values. Parker Harris, CTO of Salesforce, put some more technology meat on the Customer 360 platform.

There is more and more data that is available that can help inform businesses about their customers, and those businesses that successfully utilize these new sources and quantities of data will be able to provide a superior customer experience. However, predicting customer behavior remains very challenging. This post is the first in a series where we will go over examples of how Joe Blue, a Data Scientist in MapR Professional Services, assisted MapR customers in identifying new data sources and applying machine learning algorithms in order to better understand their customers. The first example in the series is an advertising customer 360; the next blog post in the series will cover banking and healthcare customer 360 examples. MapR works with companies who have solved business problems but are limited with what they can do with their data, and they are looking for the next step.