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Enhancing customer care through deep machine learning at Travelers

CIO

Collectively, the scope spans about 1,600 data analytics professionals in the company and we work closely with our technology partnersâ??more that cover areas of software engineering, infrastructure, cybersecurity, and architecture, for instance. But we have to bring in the right talent. more than 3,000 of themâ??that

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Coalesce lands fresh capital to transform data at ‘enterprise scale’

TechCrunch

.” Coalesce offers tools designed to simplify modeling, cleansing and governance of data primarily in the Snowflake cloud, powered by what Petrossian describes as a “column-aware” architecture that leverages metadata to manage data transformations with an understanding of how the data is related or connected.

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Modernizing Data Pipelines using Cloudera Data Platform – Part 1

Cloudera

To keep up, data pipelines are being vigorously reshaped with modern tools and techniques. At Cloudera, we recently introduced several cutting-edge innovations in our Cloudera Data Engineering experience (CDE) as part of our Enterprise Data Cloud product — Cloudera Data Platform (CDP) — to serve the growing demands.

Data 88
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Building a Scalable Search Architecture

Confluent

As soon as the number of data points involved in your search feature increases, typically we’ll introduce a broker in between all the involved components. This architectural pattern provides several benefits: Better scalability by allowing multiple data producers and consumers to run in parallel.

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How Retailers Use Artificial Intelligence to Innovate Customer Experience and Enhance Operations

Altexsoft

Experts from such companies as Lucidworks, Advantech, KAPUA, MindsDB, Fellow Robots, KaizenTek, Aware Corporation, XR Web, and fashion brands Hockerty and Sumissura joined the discussion. X-Mart visitors can choose from a wide range of items, including beauty products and fast-moving consumer goods, as well as fashion and apparel.

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Bringing an AI Product to Market

O'Reilly Media - Ideas

For example, an AI product that helps a clothing manufacturer understand which materials to buy will become stale as fashions change. Nonetheless, building a superior feature pipeline or model architecture will always be worthwhile. Another scoping consideration concerns the processing engine that will power the product.

Marketing 145
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The Year Ahead for BPM -- 2019 Predictions from Top Influencers

BPM

Now we’re seeing AI dominating the conversations (without a lot of actual adoption in the early majority), and RPA creating a lot of buzz, though companies adopting it are starting to realize that scaling an RPA based automation architecture is flawed by design. This requires a new architecture capable of true scale and speed.