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Cédric CarboneBertrand DiardJean Michel FrancoYves de MontcheuilGavin TargonskiMike Tuchen

Key Capabilities of MDM for Lean Managed Services (MDM Summer Series Part 8)

August 21, 2014 - 04:30 - Jean-Michel Franco

In this “summer series” of posts dedicated to Master Data Management for Product Data, we’ve gone across what we identified as the five most frequent use cases of MDM for product data. Now we are looking at the key capabilities that are needed in MDM platform to address each of these use cases. In this post, we address the MDM for lean managed services , which is about creating and orchestrating a standardized and unified infrastructure from a heterogeneous landscape of legacy assets.

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Key Capabilities of MDM for Material Data (MDM Summer Series Part 7)

August 18, 2014 - 04:30 - Jean-Michel Franco

In this “summer series” of posts dedicated to Master Data Management for Product Data, we’ve gone across what we identified as the five most frequent use cases of MDM for product data. Now we are looking at the key capabilities that are needed in MDM platform to address each of these use cases. In this post, we address the MDM for Material Data.

As we will further discover through this post, strong data integration and data cleansing capabilities will be needed, together with the ability to model and maintain a uniform semantic view of the data across multiple models inherited from legacy applications and/or commercial off the shelf software. Standardization capabilities are important too, so that product can be easily browsed and searchable and product data can be electronically shared between business partners or regulation authorities when applicable. Strong stewardship capabilities will be needed as well.

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MDM for Anything (MDM Summer Series Part 6)

August 14, 2014 - 04:30 - Jean-Michel Franco

In this “summer series” of posts dedicated to Master Data Management for Product Data, we go across what we identified as the five most frequent use cases of MDM for product data.

After reviewing all the other use cases, there is what I call MDM for “anything”.  This is in fact not a real facet, because the only common point of the product data that goes in this category is that they don’t belong to the aforementioned categories.

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Product Information Management (MDM Summer Series Part 5)

August 11, 2014 - 04:30 - Jean-Michel Franco

In this “summer series” of posts dedicated to Master Data Management for Product Data, we go across what we identified as the five most frequent use cases of MDM for product data. In this post, we focus on the Product Information Management use case.

Product Information Management (PIM) is the most popular use case of MDM for Product Data. For companies that distribute off-the-shelf products, this has become a must, especially where those products are distributed across multiple channels. This is probably why this use case drives so much attention from solution vendors, even if it applicable only in some industries.

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MDM for Regulated Products (MDM Summer Series Part 4)

August 7, 2014 - 04:30 - Jean-Michel Franco

In this “summer series” of posts dedicated to Master Data Management for Product Data, we go across what we identified as the five most frequent use cases of MDM for product data.

In this fourth part of the series, we focus on MDM for Regulated Products. This use case happens when products must comply with government or industry regulations.  This mandates to adhere to standard codifications and to exchange information beyond the enterprise walls to provide control and traceability on how products are sourced, tested, manufactured, packaged, documented, transported or promoted.

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MDM for Lean Managed Services (MDM Summer Series Part 3)

August 4, 2014 - 04:30 - Jean-Michel Franco

In this “summer series” of posts dedicated to Master Data Management for Product Data, we go across what we identified as the five most frequent use cases of MDM for product data.

This post focuses on MDM for Lean Managed Services,  a use case that we are seeing in companies that operate an infrastructure composed of a large number of equipment. For example, this can be a facility manager that operates a set of devices to deliver IT or network capabilities to its customers; or a utility provider that manages a networked grid; or a provider of Maintenance, Repair and Operations related services. This also applies for enterprises that are providing support and services for their product line.

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#BigDataWithTalend: Customer Service Analysis with Hadoop

August 1, 2014 - 03:14 - Yves de Montcheuil

We asked Hadoop Summit attendees to share their big data story.

In this short sequence, Therian Webb of ClickFox provides insight on customer service data analysis.

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MDM for Material Data (MDM Summer Series Part 2)

July 30, 2014 - 22:33 - Jean-Michel Franco

In this “summer series” of posts dedicated to Master Data Management for Product Data, we go across what we identified as the five most frequent use cases of MDM for product data.

In this post, we focus on MDM for Material Data; it aims to manage centrally information about spare parts, raw materials and final products, and then share this trusted and unified view across organizations, processes and information systems.

MDM for Material Data is seen in industries that engineer, procure, manufacture, store, sell and configure products. Typically, this is what defines the manufacturing industry. Material refers to potentially any inventory items that can be uniquely identified by an SKU (Stock Keeping unit), from the raw material to the finished goods, so the focus is not, or not only, the customer facing side of the product.

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A Short Summary of Talend Big Data, Live from the Pacific Northwest BI Summit

July 29, 2014 - 11:05 - Yves de Montcheuil

Few vendors are invited by Scott Humphrey to this annual gathering of data gurus – and for the past six years, I have had the privilege to represent Talend.  As posts from previous years attest, this is an event rich in discussions and brainstorming. This is also a unique event where we get the opportunity to sit down with analysts for fireside discussions (without the fire, clearly not needed in July in Oregon).

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#BigDataWithTalend: Discover Supplements ETL with Big Data

July 29, 2014 - 00:11 - Yves de Montcheuil

We asked Hadoop Summit attendees to share their big data story.

In this short sequence, Alex Marshall of Discover Financial Services provides insight on reducing costs with the help of big data.

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