Tag Archives: Hadoop

The Safe On-Ramp to Big Data

The hype around big data is certainly top of mind with executives at most companies today but what I am really seeing are companies finally making the connection between innovation and data. Data as a corporate asset is now getting the respect it deserves in terms of a business strategy to introduce new innovative products and services and improve business operations. The most advanced companies have C-level executives responsible for delivering top and bottom line results by managing their data assets to their maximum potential. The Chief Data Officer and Chief Analytics Officer own this responsibility and report directly to the CEO. (more…)

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Aligning Big Data with MDM

In my recent blog posts, we have looked at ways that master data management can become an integral component to the enterprise architecture, and I would be remiss if I did not look at how MDM dovetails with an emerging data management imperative: big data and big data analytics. Fortunately, the value of identity resolution and MDM has the potential for both contributing to performance improvement while enabling efficient entity extraction and recognition. (more…)

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Evolving from Chaos to Competitiveness: The Emerging Architecture of Next-Generation Data Integration

To compete on Big Data and analytics, today’s always-on enterprise needs a well-designed evolving high-level architecture that continuously provides trusted data originating from a vast and fast-changing range of sources, often with different formats, and within different contexts.

To meet this challenge, the art and science of data integration is evolving, from duplicative, project-based silos that have consumed organizations’ time and resources to an architectural approach, in which data integration is based on sustainable and repeatable data integration practices – delivering data integration automatically anytime the business requires it. (more…)

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My Thoughts on Gartner’s Thoughts About the Challenges of Hadoop for Data Integration

Just read a great Gartner report titled “Hadoop is Not a Data Integration Solution” (January 29, 2013). However, I beg to differ slightly with Gartner on this one. The title should have been “Hadoop Alone is Not a Data Integration Solution.” The report outlines all of the reasons that just deploying Hadoop by itself is often quite challenging.

Issues that we at Informatica have personally seen our customers deal with include: (more…)

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Big Data is Your Data – Are You Ready?

What is big data? Simply put, it’s data that is big, it’s your data when it gets big.  And for most of you, that’s already happened or inevitable. Regardless of how you define big data, a more important question is “Are you ready for big data?”.  Without some careful consideration of your data architecture, when faced with big data challenges you may find yourself writing some big checks as you scramble to address the new demands on your business.  Fortunately not all is lost.  As many Informatica customers have already learned, next generation data integration can help arm you to handle big data without  ripping and replacing your existing data integration architecture.  (more…)

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How to Avoid the Big Data Trough of Disillusionment

Has big data entered the “trough of disillusionment?” That’s what I’ve heard recently. Like  many hyped up technology trends the trough can be deep and long as project failures accumulate, or for ‘hot’ trends that evolve and mature quickly the trough can be shallow and short, leading to broader and rapid adoption. Is the big data hype failing to deliver on its promise of increased revenue and competitive advantage for companies that leverage big data to introduce new products and services and improve business operations? Why is it that some big data projects fail to deliver on their promise? Svetlana Sicular, Research Director, Gartner points out in her blog Big Data is Falling into the Trough of Disillusionment that, “These [advanced client] organizations have fascinating ideas, but they are disappointed with a difficulty of figuring out reliable solutions.” There are several reasons why big data projects may fail to deliver on their promise: (more…)

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Search Advertising – The New Marketing Mantra

Search Advertising also known as Search Engine Marketing (SEM), is a totally unique medium for attracting new customers. It is a method of placing online advertisements on Web pages that show results from search engine queries. Through the same search engine advertising services, advertisements can also be placed on Web pages with other published content. It is a multi-billion dollar industry. Advertising on Google, Yahoo and MSN gives you a total reach of roughly 86.4% of all Internet users. With such a broad reach, Search Advertising is one of the most extensible forms of advertising available, with added benefits that other forms of advertising are lacking.

In Search Advertising advertisers pay the website owner for clicks on their ads. There are two major types of Search Advertising: Sponsored Search and Content Placement Targeting. (more…)

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NYSE + ICE = Double Derivatives Power?

Right before Christmas, I was delighted to read about the proposed merger between the New York Stock Exchange and Intercontinental Exchange. ICE and  NYSE have been customers that we on the Informatica Ultra Messaging team have been working with for several years. NYSE Technologies leveraged our high performance messaging as part of their direct feeds market data solution that lowered latencies across dozens of Wall Street firms around the globe. (more…)

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Building the Business Case for Big Data: Learn to Walk Before You Run

In a recent webinar, Mark Smith, CEO at Ventana Research and David Lyle, vice president, Product Strategy at Informatica discussed: “Building the Business Case and Establishing the Fundamentals for Big Data Projects.”  Mark pointed out that the second biggest barrier that impedes improving big data initiatives is that the “business case is not strong enough.” The first and third barriers respectively, were “lack of resources” and “no budget” which are also related to having a strong business case. In this context, Dave provided a simple formula from which to build the business case:

Return on Big Data = Value of Big Data / Cost of Big Data (more…)

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