Big Data Blog

Bloggers

Cédric CarboneBertrand DiardJean Michel FrancoEdward OstAshley StirrupGavin TargonskiMike Tuchen

Takeaways from the new Magic Quadrant for Data Quality Tools

December 9, 2014 - 00:38 - Jean-Michel Franco

Gartner has just released its annual “Magic Quadrant for Data Quality Tools.”[1]

While everyone’s first priority might be to check out the various recognitions, I would also recommend taking the time to review the market overview section. I found the views shared by analysts Saul Judah and Ted Friedman on the overall data quality market and major trends both interesting and inspiring.

Hence this blog post to share my takeaways.

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What Is a Container? (Container Architecture Series Part 1)

December 2, 2014 - 01:24 - edward ost

This is the first in a series of posts on container-centric integration architecture.  This first post covers common approaches to applying containers for application integration in an enterprise context.  It begins with a basic definition and discussion of the Container design patterns.  Subsequent posts will explore the role of Containers in the context of Enterprise Integration concerns.  This will continue with how SOA and Cloud solutions drive the need for enterprise management delivered via service containerization and the need for OSGI modularity.  Finally, we will apply these princ

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More Action, Less Talk - Big Data Success Stories

November 13, 2014 - 07:09 - Ashley Stirrup

The term ‘big data’ is at risk of premature over-exposure. I’m sure there are already many who turn off when they hear it – thinking there’s too much talk and very little action. In fact, observing that ‘many companies don’t know where to start with big data projects’ has become the default opinion within the IT industry.

I however stand by the view that integration and analysis of this big data stands to transform today’s business world as we know it. And while it’s true that many firms are still unsure how and where to begin when it comes to drawing value from their data, there is a growing pool of companies to observe. Their applications might all be different; they may tend to be larger corporations rather than mid-range businesses, but there is no reason why companies of any size can’t still look and learn.

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Turning a Page

October 18, 2014 - 05:15 - Yves de Montcheuil

At the end of October, I will be leaving Talend, after more than 7 years leading its marketing charge. It has been quite a ride – thrilling, high octane, wearing at times, but how rewarding.

And indeed, how rewarding it is to have witnessed both the drastic change of open source over the years, and the rise of a true alternative response to integration challenges.

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Data Quality Everywhere

September 23, 2014 - 04:30 - Jean-Michel Franco

Data Quality follows the same principles than other well defined quality related processes: it is all about engaging an improvement cycle to Define & detect, Measure, Analyze, Improve and Control quality.

This doesn’t happen at one time, or one place. It should be an ongoing effort, and that is often neglected when dealing with data quality. Think about the big ERP, CRM or IT consolidation projects where data quality gets high attention during the roll out, and then fades away once the project is delivered.

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Welcoming our New Head of Engineering

September 10, 2014 - 07:47 - Mike Tuchen

Today marks a major new milestone in Talend’s journey: we’re thrilled to announce that Laurent Bride is joining us as CTO.  Laurent is both a terrific manager and leader as well as a strong technologist who brings a wealth of experience to lead our engineering team in the coming years.  Most recently, Laurent was CTO at Axway and was responsible for R&D, Innovation and Product Management. His role was to take Axway’s products to the next level while ensuring quality and security of the solutions. Laurent was also very involved in M&A and post-integration activities.  Laurent has spent more than nine years in the Silicon Valley, with Business Objects and then SAP. During his tenure, Laurent has developed deep expertise in Enterprise Software Development, working with multi-national teams across the globe. His last role at SAP was SVP of Advanced Development, leading a 350 person team of developers building the next generation mobile, cloud, real-time analytics, M2M and big data solutions.  Laurent holds an engineering degree in mathematics and computer sciences from EISTI.

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Key Capabilities of MDM for Anything, and Wrap-up (MDM Summer Series Part 11)

August 29, 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. Then, we looked at the key capabilities that are needed in MDM platform to address each of these use cases. In this last post of the series, we address the key capabilites needed for MDM for Anything, which is about dealing with the things that you are producing and/or the things that you using to produce them, for things that don’t fit to the four other facets of product master data described in this series.

MDM for anything refers to all the master data about product and things that are very specific to an industry, a use case, an enterprise… As this is specific, you would have to define on a case by case basis what is needed from your MDM solution, in terms of modeling, data quality, data accessibility, data stewardship, master data services... In any case, the flexibility of the solutions will key. By flexibility, I mean that the MDM solution should allow designing very specific data models, to connect easily to any source of data and eventually to applications in real time. 

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MDM for Product Information Management needs both a strongKey Capabilities of MDM for Product Information Management (MDM Summer Series Part 10)

August 27, 2014 - 04:06 - 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 Product Information Management, which is about managing the customer facing side of build to stock products.

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Key Capabilities of MDM for Regulated Products (MDM Summer Series Part 9)

August 25, 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 Regulated Products, which is about using MDM to support compliance to regulations related to products or facilitate data exchange related to products between business partners.

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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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