Tag Archives: Gartner

Gartner Estimates Growth for MDM Market and Positions Informatica as a Leader in The Magic Quadrant for Customer Data Solutions

Over the last few weeks I’ve been saying that the incredible popularity of our MDM-related events is a sign that MDM is a vital and growing market. Now I consider it reassuring that analysts agree. It’s also reassuring to see Informatica positioned as a Leader in the Magic Quadrant for Master Data Management of Customer Data Solutions, a position that Informatica has held for four years in a row.

In Gartner’s October 2013 Magic Quadrant for Master Data Management of Customer Data Solutions, analysts Bill O’Kane and Saul Judah estimates that the total software revenue for packaged MDM solutions was $1.6B in 2012, an increase of 7.8% from 2011, as compared with a 4.7% rise for the overall enterprise software market. Further, O’Kane and Judah estimate that the MDM of customer data solutions market segment was worth $527M in 2012, an increase of 5.4% from 2011. The analysts go on to say that the customer MDM market is far from mature, and that just 40% of the organizations surveyed by Gartner were beginning MDM initiatives.

One of MDM’s most important benefits is a single view of the customer across company departments and siloed systems. In this Magic Quadrant report, the analysts describe some of the business drivers for obtaining this view. For the banking and life sciences sectors, the analysts include “Compliance and risk management drivers, such as ‘know your customer,’ anti-money laundering and counterparty risk management in the banking sector, and Sunshine Act compliance in the life sciences sector.” I believe that many other industries could similarly benefit from trusted customer interactions. Another set of drivers they list are “cost optimization and efficiency drivers,” and finally, “revenue and profitability growth drivers,” explaining that examples of such drivers include “initiatives to improve cross-selling, upselling, and retention.”

Finally, the analysts observed a trend which we believe supports Informatica’s view of the importance of all-encompassing MDM solutions that can manage master data across enterprise. As noted in the report, “Many organizations have now invested in creating a new central system to master their customer data, with the majority (an estimated 80%) of organizations buying packaged MDM of customer data solutions, as opposed to building the capability themselves.”

To learn more about Gartner’s October 2013 Magic Quadrant for Master Data Management of Customer Data Solutions, see our press release or download the full report. After reading the report, please share your thoughts below.

 

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

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Has MDM Crossed the Chasm? Musings of a Marketer at Gartner MDM Summit

The general feeling, at the recent Gartner Master Data Management Summit, was one of excitement. It wasn’t just that this was the largest MDM Summit to date with 600+ registrants; it was also the buzz in and around the convention center. The conversation wasn’t about promises and “what ifs,” it was about tactics, and 2nd or even 3rd generation MDM initiatives. This growth is a sign that MDM has matured past the initial phase of high expectations, in Gartner’s hype cycle. To put it in Geoffrey Moore’s terms, I think it’s a sign that MDM has crossed the chasm from early adoption to more widespread, pragmatic adoption.

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Big Product Data: Leverage the Best Content Merge for Better Customer Service

According to a Forbes article, the average organization will grow their data by 50 percent in the coming year. Overall corporate data is expected to grow by 94 percent. According to Informatica, data is predicted to increase by as much as 75 times the current volume by the year 2020. What is Big Data all about? Big Data is the management and analytics of an immensely growing volume, variety, and velocity of data in a digital world. A precise definition of big data from analysts like Gartner and Forrester is a hot topic right now that is covered in a lot of blogs.

In my point of view, big data is connecting the dots. It is connecting more than ever before. But what is the role of product data in a big data world?

After recently talking to our customer Halfords, the UK retailer for bicycle and auto parts revealed: All challenge Amazon. Halfords is known as the expert and friend for cyclists. Therefore they position their brand as the leading expert with the best information. They use product information as a differentiator in the market to gain customers’ trust.

This article refers to a challenge that a lot of distributors and retailers are facing. In order to better serve their B2B and B2C customers, they grow and position their product range to be the one trusted supplier. The long tail (endless aisle) strategy offers higher margins with niche products as well.

These distributors and retailers are faced with the challenge of handling 100s or 1000s of suppliers providing content for millions of products. What happens when different suppliers provide information for the same product?

A business case of big product data: Innovative distributors attempt to merge different product content to create the best and richest product information. This requires an intelligent analysis of a supplier’s product data, and intelligent automatism in order to merge this data to create superior product content. The role of the data steward in defining these rules and policies becomes more important than ever before.

How can this be solved?

Data doesn’t only come from suppliers but from other data sources as well. Basic product information might come from a data hub like GS1 or could be synchronized from the distributor’s ERP system, which in turn might be leading the creation of new products in the distributor’s master assortment.

This basic data will be enriched by data coming directly from the manufactures or the suppliers of the distributor. These different data sources provide content for the same products in different levels of quality, richness, and completeness.

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Which parts of product information are used from which data sources is determined by objective data quality rules combined with a definition of trust specific to each data source. One supplier is known for accurate descriptions in English while another provides the better German information. And yet a third data source usually provides the best images.

Governance of Product Information Creates Competitive Advantages

This is when Product Information Management comes into the field: to control big product data. According to Heiler’s PIM Product Manager, Markus Schuster, these business processes can only be successful when used with intelligent, highly automated data quality proofpoints and workflows that adhere to the data governance policy.

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A Case for Universal MDM: The Federation of Point-MDM Solutions

I’m at Barcelona this week for the European Gartner MDM Summit. I had a chance to catch up with one of the Gartner MDM analysts before the event, and we had a discussion about the growth of MDM.  He mentioned that MDM will become pervasive within the enterprise as organizations expand its use as a necessary foundation for governing all of their business-critical master data such as customers, products, and so on.

To solve their business problems accurately, companies seek targeted MDM solutions. For e.g., retail, distribution, and manufacturing companies use PIM for merchandising, distributing products, and supplier on-boarding, while financial services, healthcare, and high tech companies use customer MDM with their CRM, such as salesforce.com, for improving customer segmentation, cross-sell , and up-sell. (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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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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Informatica Named a Leader in Data Masking Gartner Magic Quadrant

Informatica was listed as a leader in the industry’s first Gartner Magic Quadrant for Data Masking Technology. Finally, the data masking market gets a main stage role in one of the fastest growing enterprise software markets – data security. With the incredible explosion of data and the resulting number of places our personal information exists in the cybersphere, this confirmation is desperately needed as we enter into 2013. (more…)

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Let Your Data Scientists Be Scientists

With the rise in popularity of the elusive and expensive data scientist it’s very sad that once a data science team is assembled (at a very high recurring cost to the company I may add) that they spend most of their time doing work they weren’t really hired to do in the first place. That’s right! It turns out that data scientists spend only about 20% of their time doing real analysis – that is the work they were trained to do. How is the other 80% of their time spent? (more…)

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The Report of My Death Was an Exaggeration

“The report of my death was an exaggeration.”

– Mark Twain

Ah yes, another conference another old technology is declared dead.  Mainframe… dead.  Any programming language other than Java…. dead.  8 track tapes …OK, well some things thankfully do die, along with the Ford Pinto that I used to listen to the Beatles Greatest Hits Red Album over and over again on that 8 track… ah yes the good old days, but I digress. (more…)

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Will Salesforce be the Catalyst to Propel MDM into the Cloud?

Salesforce.com – a company that has become synonymous with the cloud – acquired over 100,000 customers and one million users within a span of just 10 years. Compare that to a traditional company like General Electric, the only company to be on the Dow Jones Index for over 100 years – it took them over five-times that many years to acquire the same number of customers. This goes to say that customers have been enamored by the cloud and its benefits – no software maintenance, rapid time-to-value, and subscription pricing – to name a few. No wonder, there are thousands of cloud applications and millions of users out there now. I’ve seen projections that the cloud computing market will grow to $241 billion by 2020. This might be a conservative estimate.

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Posted in Cloud Computing, Customer Acquisition & Retention, Data Governance, Data Integration Platform, Enterprise Data Management, IaaS, Master Data Management, Uncategorized | Tagged , , , , , , , , , , , , , , , , | 2 Comments