When Big Data Becomes More Valuable Than Your Products/Services

A recent global study across 1000 executives conducted by EMC and Capgemini reports the following: “64% of respondents said that big data is changing traditional business boundaries and enabling non-traditional providers to move into their industry, and over half (53%) expect to face increased competition from start-ups enabled by data.”

My take: Eventually any company expecting to compete effectively must become a software company, where data is the primary asset driving business strategy and revenue. Going a step further, by monetizing big data, companies are creating new revenue streams that will actually eclipse the value of a company’s existing products or services over time. This is supported by the EMC and Capgemini study as well: “Among our respondents, 63% consider that the monetization of data could eventually become as valuable to their organizations as their existing products and services.”


The question is how to find gold in the flood of data flowing in and out of the organization to compete effectively, especially against new digital startups. To answer this question, I spoke to Capgemini’s Global Vice President for Big Data Steve Jones who strongly believes the answer lies within the power of a business data lake.

1.  As an industry leader in big data, what is so exciting about a data lake solution?

I’d like to first define what we coined a ‘business’ data lake back in 2013, which is an architecture that supports big, fast, and managed data. Managed data is key since it is the data that is managed or governed in line with business objectives.

What’s exciting about a business data lake is that enables organizations to achieve a very important goal – uncovering new business models through big data analytics. Generating new revenue streams is the primary differentiator between a successful and unsuccessful business.

Because the data is governed in line with the business, organizations have more flexible control of the data to make it accessible for analysis across the entire organization. Business units are no longer constrained by traditional reporting platforms, but rather, can freely discover and distill the information they need to uncover insights. These traditional reporting platforms were sufficient for specific uses in the past, but now there is a new generation of data driven companies creating unprecedented competition. This is why companies need a fundamentally new architecture such as a business data lake to challenge the competition.

2.  Tell us why customers looking to transform their business with big data should work with Capgemini.

Through our experience with big, fast, and managed data, we were the first understand the changing landscape and create the ‘business data lake’ approach. We published the first reference architecture that not includes the technology components, but also the business factor or change that needs to occur to make the business data lake effective.

So not only do we have the experience, but we also have the vision that is needed to help organizations make a fundamental transformation in how they manage, execute, and derive business value from data. This is a multi-year transformation that requires you to work with an experienced partner that helps set the vision and closely works with you over time to achieve results. Again, this includes both the technology and business transformation that needs to occur across the organization.

3.  Why has Capgemini become a premier partner of the EMC Business Data Lake?

Back in 2012 we recognized that big data transformation wasn’t happening fast enough because our large customers were not achieving business results and needed more support. Unlike technology powerhouses such as Facebook, Yahoo, and Google, a typical customer is not equipped to custom engineer a big data solution to support their business needs.

We knew an industrialized approach was the answer to get our large customers transformed and compress the time to value. The EMC Business Data Lake is this approach, providing fully-engineered solution that is simple to deploy and operate. We also like its open partner ecosystem approach since it allows our customers to use products and tools they already have.

4.  What makes EMC Business Data Lake a successful, fully-engineered solution?

EMC recognized that a single company alone is unable to provide an industrialized solution. Instead, they utilized the Federation and developed a partner ecosystem to collaborate and engineer a business data lake solution to remove the headaches and cost of integration. Pre-configured building blocks, core Federation technologies and an open ecosystem allows a typical customer to quickly adopt and subsequently transform.


5.  What customers are the ideal candidates for the EMC Business Data Lake?

Any customer that doesn’t want to set up a specialized IT team just to handle data such as setting up and managing a Hadoop clusters since this requires huge budgets and resources. Also, an ideal customer is one that prioritizes business innovation over technology innovation, since this solution compresses the time to value through rapid deployment.

Destination Data Lake: Accelerating the Big Data Journey

Most people understand that big data and analytics can have a positive impact on their business. What trips them up is how to make that happen. EMC’s answer to that complex challenge is the EMC Business Data Lake, the industry’s first fully engineered, enterprise-grade data lake that’s redefining big data.  For details, check out the virtual launch event.


I spoke with Aidan O’Brien, Senior Director of EMC’s Strategic Big Data Initiative, and asked him why he’s excited about EMC Business Data Lake and why it sets precedence in the world of big data analytics.

1.  What are extraordinary outcomes companies may achieve with big data analytics?

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Innovating The Marketing Process With A Data Lake

Like many global companies, EMC depends heavily on a CRM to manage sales and purchasing data about its vast global installed base. Over time, we realized that without big data analytics, this customer data was trapped inside our systems and providing limited value.


EMC decided that offering analytical capabilities through a data lake architecture would substantially increase the value of this data. To get there, EMC hired Todd Forsythe, EMC Vice President, Corporate Marketing, to create the Marketing Science Lab. I spoke to Todd about why he is so excited about the impact of big data and the Marketing Science Lab on sales and marketing:

1. What is the Marketing Science Lab?

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Want To Build A Data Science Team? EMC Offers a Holistic Approach

Many of our customers invest in big data solutions to target their sales prospects better, explore advanced medical research, and make their internal processes more efficient. The biggest obstacle to getting these initiatives out of the gate is the shortage of big data skills within their own firms and across the industry.

To address this skills gap, EMC has developed a thorough data science and big data analytics curriculum for our customers. EMC was one of the first companies to offer data science education with rigorous, live instruction using free and open source tools. As of today, more than 10,000 customers, partners, and college students have attended the training.


I spoke with EMC’s David Dietrich, who leads this unique program to discuss his approach to data science education, which differs from more traditional product-oriented education. What I found most interesting is that in addition to David’s work at EMC, he has also helped design big data analytics curricula for Babson College and other universities.  More recently,  David has published a book, Data Science and Big Data Analytics, to help further develop data science skills and expertise in the industry.

1.  Why is EMC pushing so hard to educate and develop data scientists?

As an information company, we’re extremely attuned to the value of big data, which is exploding in both the sheer amount and how organizations in virtually every field and industry are using it to solve critical problems. When EMC acquired our first big data company, Greenplum, several years ago, we quickly became aware that there was a shortage of people who had the data science and business skills to help companies utilize big data.

2.  How is EMC taking a holistic approach to data science education?

We recognize that learning how to use big data technology alone does not ensure success. Senior management must make sure that appropriate people and processes are in place to drive the change and innovation necessary for valuable big data results to occur. To help companies on their journey, we offer courses for data scientists, who execute big data projects, and business executives who sponsor, run and manage them.

Our goal is to educate all levels of an organization so that data scientists and business people understand one another. That way, the organization is able to roll out big data projects with greater adoption and success. In addition to offering courses to our customers, we also work closely with universities and educational institutions to help them develop their own curriculum and programs.

3.  Please describe some of the important skills for aspiring data scientists.

Working in strategy and analytics for the past 20 years, I’ve always been drawn to experimenting with data to solve problems, which is exactly is the mindset you need to tackle big data. Companies often ask me how to go about using massive amounts of structured and unstructured data to solve business problems. How do they know what to choose and ignore? How do they know what algorithms to apply? Our courses encourage a culture of experimentation that leads to answering these questions. We teach our students how to test an idea with data, measure it quantitatively, learn from it and iterate. This test and learn mindset is critical to becoming a talented data scientist and data-driven organization.

4.  What are some of the challenges with evolving into a data-driven organization?

There can be a substantial divide between data scientists and business people who manage and work with them on big data projects. Many business people lack the technical background to understand how the algorithms apply to the problem and how to test ideas with data. And some data scientists may not understand the business context. We’re trying to educate each side so they can get a clearer picture and drive toward common goals. Once you bridge that gap, you can start driving real change, and solving old problems with big data or new information sources that were once unusable.

5.  What should companies expect after they have successfully made the leap to big data?

We’re educating them in how to train and staff a big data team, as well as build processes to be effective and successful. With this approach, companies can more effectively define the business problem, acquire the right data sets, experiment, communicate the results, and finally, operationalize the new processes.