Tag Archives: mdm in a big data world

MDM in a Big Data World – ON TOUR

Ed. Note: Our own Harj Dhillon shares his thoughts on Informatica World Tour in Boston below.

It was a full house.  Over 100 people attended the Informatica World Tour city stop in Boston on November 19th, where our CTO, Chris Blotto, keynoted a session on “MDM in a Big Data World.”

The objective of the session was to educate business and IT practitioners on top-of-mind topics, such as data lakes, security, cloud adaption, and MDM. Our partner, Informatica, shares a common vision in viewing data as valuable enterprise asset, with their product suite purpose-built to move data quickly, securely, and with traceability to the end user.

Continue reading MDM in a Big Data World – ON TOUR

Chris Blotto to Speak on MDM in a Big Data World at Informatica World Tour

Knowledgent’s CTO, Chris Blotto, will be speaking at the Boston stop on the Informatica World Tour on Wednesday, November 19 at the Sheraton Boston Hotel. During the Informatica World Tour, industry experts will discuss innovations that will take the concept of a data platform to an entirely new level. Attendees will learn about technology shifts that are propelling us forward in a data-centric world – where data is not a by-product, but the fuel that powers transformations in business, society, and individual lives. With cloud applications, mobile devices, and globally dispersed teams – data is everywhere and it matters more than ever. Continue reading Chris Blotto to Speak on MDM in a Big Data World at Informatica World Tour

INFOGRAPHIC: Anatomy of a Managed Information Object

The data lake, a data-centered architecture featuring a repository capable of storing vast quantities of data in various formats, has emerged among IT organizations as a solution to the challenges with existing enterprise data architectures. In the data lake, data itself is no longer restrained by initial schema decisions and can be exploited more freely by the enterprise.

Continue reading INFOGRAPHIC: Anatomy of a Managed Information Object

5 Best Practices for Applying MDM to Non-Traditional Data

The concept that, more than any other variable, has put the “big” in Big Data, has to be the notion of uncontexted, unstructured, or non-traditional data and the potential it represents.   The term “non-traditional” when applied to data generally refers to data that does not easily lend itself to be captured in spreadsheets, tables, or relational databases. Some examples of this type of data include non-relational database data, such as documents, email, instant messaging(IM)/texting, and sensor data, and “signal” data like blogs and social media.

But non-traditional data typically can’t be captured with the same old tools or analyzed with the same old methods. Applying MDM to non-traditional data raises a different set of challenges than when dealing with traditional data. Although you will be asking some of the same questions as you would with traditional data, you may need to use a different approach or involve a completely new perspective to realize Big Data’s potential. Continue reading 5 Best Practices for Applying MDM to Non-Traditional Data

Deterministic versus Probabilistic Matching in Big Data

“Information is the new oil” is the latest trend, and like oil, crude data needs to be refined before it can be consumed. In other words, having big data won’t serve any purpose unless the data is good enough to be useful. With the potential for mismatching, duplication, and other quality threats from ingesting data across disparate sources, ensuring the accuracy and quality of data is more important than ever.

This is where big data meets Master Data Management (MDM). Based on the concept of “better to be safe than sorry,” MDM users can apply data matching techniques to resolve some data quality conflicts. Applying these techniques enables users to determine the data that is “most likely” to be correct, and if not perfect, at least at a “Fit to Purpose” level of quality. This post discusses two matching techniques, Deterministic Matching and Probabilistic, or “Fuzzy,” Matching, in the context of big data. Continue reading Deterministic versus Probabilistic Matching in Big Data

3 Takeaways from the 2014 MDM & Data Governance Summit

We hope you had an opportunity to visit NYC and the Knowledgent booth at the MDM & Data Governance Summit last week on October 5 at the Sheraton Times Square.  The MDM practitioners we spoke with found the sessions valuable and insightful. We particularly enjoyed the engaging discussions we had after our CTO Chris Blotto’s talk on “MDM in a Big Data World”.

This was the ninth year of the summit, and it’s clear that MDM is still a topic of wide interest and only becoming more relevant in a world where massive amounts of data are now available to the business.

Here are our top three takeaways from the event: Continue reading 3 Takeaways from the 2014 MDM & Data Governance Summit

Q&A with Chris Blotto on MDM, Big Data, and the Data Lake

In the era of Big Data, what role does Master Data Management (MDM) play? Our own Chris Blotto, Chief Technology Officer at Knowledgent, addressed this question at the MDM & Data Governance Summit yesterday at the Industry Innovation Lunch.

Chris’ presentation, “MDM in a Big Data World,” covered a range of topics concerning MDM and Data Governance professionals navigating the Big Data landscape.  He discussed using MDM capabilities to enable search and navigation in distributed environments, transitioning existing data management investments into the Big Data world, and distinguishing the hype from the reality through real-world use case overviews.

After his presentation, we sat down with Chris to get his thoughts on the role of MDM in today’s analytically driven environment:

Continue reading Q&A with Chris Blotto on MDM, Big Data, and the Data Lake

Knowledgent CTO to Speak at MDM & Data Governance Summit

Knowledgent’s own CTO Christ Blotto will be speaking at the MDM & Data Governance Summit at the Sheraton Times Square in New York City October 5-7. Chris is presenting “MDM in a Big Data World” at the Industry Innovation Lunch on Monday, October 6, from 11:45am to 12:45pm.

“More organizations are looking at Big Data solutions, such as the Data Lake, for managing their data, and their users need to be able to find the data they need when they need it,” explains Mr. Blotto. “As a result, there is a need for an on-demand Data and Analytics as a Service model, one that is not driven by specific analytics projects. MDM is a key enabler of this new paradigm.”

More information can be found in the press release here.