Is It All About The Data Scientist?

The answer is no. It is a holistic, team effort that involves expanding the mind and skill set of executives, business users, IT implementers, data scientists, and application developers to all work collectively to define a strategy and derive newer insight from big data.

And that is why EMC is so heavily focused on breaking down organizational silos and training professionals to become data scientists or at least think like data scientists, so that organizations transform into data savvy professionals with a data-driven culture working towards the same goal – competitive advantage.

I spoke to Louis Frolio, Advisory Technical Ed Consultant for EMC Big Data Solutions, how as part of a team in EMC Education Services is creating a massive professional transformation through a MOOC – Massive Open Online Course. Data Lakes for Big Data MOOC gives you an opportunity to become a data savvy professional and take on a big data or data science role in your organization at absolutely no cost.

The course kicked off May 11, but you still have plenty of time to enroll and complete the course to earn a certificate before June 8. The top 500 students (based on cumulative grade for the MOOC) will receive an electronic copy of the Data Science book just released by EMC Education Services.

1.  What is a MOOC and what is the goal of this education format? Why was it used for this course?

Over the past several years, a new trend in Education Delivery has slowly gained traction. “Classroom Flipping”, aka MOOC (Massive Open Online Course), involves delivering courses to very large numbers of students (upwards of 40,000), all at once via the internet. The term “flipping” is used because the students consume the lectures and materials at their leisure and use the MOOC platform to do homework, assignments, and interact with other students and instructors – The opposite of a traditional classroom experience.

In a MOOC, instructors develop the curriculum but do not teach it live. The educational material can be video, interactive eLearnings, literature, plus much more. The content is delivered asynchronously, meaning the students can consume the material at their convenience. What makes a MOOC so great is that it provides a place for students to engage and learn from each other.

My role as an instructor in the “Data Lakes for Big Data” MOOC is to engage students in the forums, answer questions, and foster collaboration between the students. The Emerging Technology Education group within EMC Education Services chose a MOOC for its “Data Lake for Big Data” course because it fits into a blended learning model approach to technical education and training.

2.  Who should attend this course and what value will this education bring to the organization after the 4 week course?

This course was designed with a single demographic in mind – Anyone who wants to know more about Big Data and Data Lakes. There are no pre-requisites for this course outside of a genuine interest in these emerging technologies and a desire to learn.

At the conclusion of this course students will have a solid foundation of knowledge to build upon which can include the EMC Certified Data Science and Big Data Analytics track. More importantly, students will be fully equipped to recognize and speak to big data challenges within their organizations. We fully expect that students completing this course will be able to demonstrate the value of big data and data science to their management teams.

3.  What is your role at EMC and what other EMC Education is available for burgeoning data scientists and professionals looking to expand their skill set for big data?

I have a pretty cool job. I am part of EMC’s Big Data Solution’s team where my primary objective is to distill and impart the seemingly complex subjects of Big Data Analytics and Data Science to both technical and non-technical audiences. This is made easier for me because I am also embedded in the Data Science team in the Emerging Technologies Education group within EMC Education Services. There I help develop technical training material for EMC’s Certified Data Science curriculum. If I could sum up what I love and do best it is this: I craft and narrate the story of Big Data Analytics and Data Science for everyone.

EMC Education Services has a full complement of courses for Big Data Analytics and Data Science. This includes certification in data science at the Associate level and, most recently, at the Specialist level. There is also training on Hadoop administration, Hadoop programming, and much more.

4.  Week 3 of the MOOC dives into the EMC Federation Business Data Lake. Explain to the readers what value this solution brings to Data Scientists, IT Implementers, and Executives.

The EMC Federation Business Data Lake (FBDL) is leading the vanguard in Big Data Analytics enablement, bringing together data, analytics, and applications into a fully-engineered solution. IT can deploy faster, data scientists gain insights faster, and executives see value faster.

With the rise of Big Data, we are seeing more and more software applications being defined by data and data analytics. With FBDL, it is possible to quickly build the data driven applications needed to empower organizations to extract more insights and realize more revenue from the data that is already in their data centers.

5.  What feedback have you received so far from the MOOC? Is it too late to enroll?

The feedback from the “Data Lakes for Big Data” MOOC has been nothing short of extraordinary! The overwhelming sentiment from the students has been extremely positive. A common thread amongst the feedback is that the material is extremely interesting and that the students are learning things about big data of which they were unaware. They are thrilled that this course is being offered now and that it is free. It is the right course at the right time.

It is not too late to join the MOOC. Students can complete the required tasks at any time during the four week period. The only caveat is that all the tasks have to be completed by the close of the course. Although, we are now in Week 2 and new students may feel that they may not be able to catch up, I can assure you that this is not the case. Week 1 can be completed in as little as 2-3 hours. We purposely kept week 1 light in material to give students time to familiarize themselves with the MOOC environment.

I strongly recommend that you sign up today at: educast.emc.com!

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.

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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.

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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.

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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.