Golden Gate University is located in downtown San Francisco in the heart of the Financial District. In this video, Dr. Gordon Swartz, Dean of GGU’s Ageno School of Business, reflects on the city’s reputation and position in the business world.
Dr. Swartz’s holds a DBA from Harvard University and has extensive and varied experience that combines business school teaching, research, and administration — with strategy consulting and development of high-growth organizations. As vice president of MarketBridge, Inc., he led major marketing, sales strategy, and transformation efforts for Fortune Global 500 companies.
Getting an MBA degree at GGU in San Francisco, specifically in the “FiDi”, gives students access to a wealth of expert working faculty and networking opportunities in major business areas such as finance, accounting, taxation, marketing, project management, and IT management. Throughout its 115-year history, Golden Gate University has become an integral part of the San Francisco business world — with over 16,000 alumni residing in the San Francisco Bay Area alone.
Would you please talk about your cognitive science background and your transition to business? Was this a leap?
I was part of the first attempt at cognitive science in the 1980’s, as the discipline was inventing itself. We researched psychologists of all types, computer science researchers but also linguists, philosophers and even a few math/stat folks. This afforded me the opportunity to learn about anything and not be overly focused on one approach.
At the time, I was trying to use Artificial Intelligence models (Minsky’s Frames) to understand the relationship between learning, memory and attitude change. I had social, memory and experimental psychologists as well as cognitive scientists supervising my work, which proved to be challenging as no one faculty member particularly cared about defending my work as a whole. But I picked up a little bit in a lot of areas.
These skills, when put together, helped me enter work on projects that involved things like machine learning and intelligent computer-assisted instruction with Aerospace and Defense Research and Development at Honeywell. After that, I had the opportunity to work in a data science group at Merck & Co., where I could apply my understanding of behavior change and do things like price elasticity, promotion response, and marketing experimental design.
We are using machine learning techniques to predict the likelihood of trauma-care products needed in a given region based on weather, holidays and, other predictors.
I ultimately found my way into IT where the data is created (or not), and the capability to bring advanced analytics to major problem solving and the development of people-centered solutions is enabled.
Does cognitive science have a relation to what you are doing today at Johnson & Johnson?
I would like to say that I was smart enough to know that the methods and tools I learned in graduate school would be relevant to me as Johnson & Johnson’s CIO. This is not at all the case!
There are two primary aspects of my cognitive science background that are extremely useful today.
The first is the statistical methods that we use to try to comprehend human cognitive behavior, which advances our understanding of consumers’ and patients’ behavior. We have long applied tools like predictive modeling to be able to identify what the next best action is to take.
Now, with machine learning, the system continuously and manually updates the model without human intervention. This means that the productivity of our data scientists can be greatly enhanced. With the ability to create machine learning models that extend the reach and power of each data scientist, we can leverage the creative work our professionals produce and extend it more broadly throughout the enterprise.
To lead a data science group, it is helpful if you are an “outgoing introvert”…who enjoys sharing that work with people, creating teams that do this valuable work, and persuading business leaders that this is an area well worth the investment.
How did you get into the pharma industry?
My father had a long career in marketing, which resulted in my being born in Cincinnati, Ohio, while he was working at Procter & Gamble. Because of his career, I had always been intrigued by the idea of applying cognitive science techniques to marketing. So, once I decided it was time to get serious about establishing my career, I interviewed for a variety of positions, including a marketing job at Merck & Co.
Within its U.S. business, Merck & Co. had created a small group of what we now call data scientists, where we worked on things like promotion response assessment, hospital purchase probability modeling, conjoint analysis, and extrapolative methods for product forecasting. I don’t think there was any other time in the pharmaceutical industry until now, where a company like Merck & Co. would have hired someone like me. This gave me an opportunity to join a marketing development program where I rotated through roles like managing marketing research and product management. This business foundation has been enormously useful in my career leading IT organizations.
What are the specific applications of data analytics at Johnson & Johnson?
Data science is being applied to almost every business and function within Johnson & Johnson. It is being used to help us better understand and target consumer micro-segments in order to meet our people where they are – from the grocery store to the home. It is being used in the supply chain organization to understand how to create an agile response to emerging consumer demand locally, while planning on a global basis. We are using machine learning techniques to predict the likelihood of trauma-care products needed in a given region based on weather, holidays and, other predictors. Ultimately, we are using data science to identify and create people-centered solutions that help meet our consumers’ needs.
At Johnson & Johnson, I have been involved in all areas of data analytics. We have a group of about 30 data scientists in our IT organization supporting Janssen pharmaceuticals. I have played a role in establishing a group of supply chain professionals to model the supply chain flow, end to end. And most significantly, Johnson & Johnson created technology environments that allow us to break down the complexities of modeling, and support the massive amounts of data and power required for today’s techniques.
Is there a type of person that data science appeals to?
I don’t know if there is one type of data scientist. Data science work typically requires someone who is interested in math and in understanding the relationship of metrics to the real world. It requires the type of person who gets excited about finding and quantifying relationships that no one understood before. To lead a data science group, it is helpful if you are an “outgoing introvert”. An introvert can be defined as someone who gets their energy from quiet time working alone, while an “outgoing introvert” is someone who enjoys sharing that work with people, creating teams that do this valuable work, and persuading business leaders that this is an area well worth the investment.
One of the most important soft skills required for a top-performing data scientist is the ability to understand what your business partner is trying to do… If you take the time to ask your business partners, you may be surprised at how happy they are to share their work with you.
For people who consider themselves data scientists first, what hard and soft skills do they most need in the business world?
One of the most important soft skills required for a top-performing data scientist is the ability to understand what your business partner is trying to do. If you take the time to ask your business partners, you may be surprised at how happy they are to share their work with you. You can learn a lot in a short period of time about their business strategy, about the capabilities that are needed to accomplish business objectives, and the barriers that your business faces in accomplishing those goals. Once you have this knowledge, you can aim data science techniques at overcoming the most important obstacles. If you have helpful solutions to answer your business’ most critical problems, you will find a ready audience.
Lastly, what one thing would you like people to know about your field or your work at J&J?
Many individuals know about Johnson & Johnson from our Band-Aids® and baby products. But in reality, our two largest businesses are pharmaceuticals and medical devices. We are a health technology company fueled by empathy, and we ultimately attract people who are interested in our core mission which is helping people live longer, healthier and happier lives. If you’re interested in the opportunity to contribute to humanity in this way, and would rather develop people-centered solutions then say, tune search engines or adjust hedge fund algorithms, then we have a place for you!
In this brief video, Rich Clayton, who is the VP of Oracle’s Business Analytics Product Group, describes what he calls the “massive transformation” of the business analytics market. The elements of this transformation are technology advancement, an abundance of data, the declining cost of mining and analyzing these data, and the engaged consumer.
Clayton also serves on the Advisory Board of Golden Gate University’s new Master of Business Analytics program.
Dr. Rao Mikkilineni is Chief Scientist and Co-Founder C3DNA Inc., a Silicon Valley start-up launched in 2013. He has also filled roles at Bell Systems and Hitachi. He will be teaching a class in Business Analytics Security in GGU’s Master in Business Analytics program this year.
What can you tell us about the data analytics career?
Data analytics requires data scientists who are trained in algorithms and tools that assist in extracting knowledge from raw data by correlating various items or using classification methods. The data scientists are in demand. For example, a search of LinkedIn shows that there are 1600+ jobs for data scientists at Microsoft right now (3/30/17).
Business Analytics is often written about in the context of consumer transactions. What is the connection to data security?
Information security is about protecting confidentiality, integrity, and availability of data, which is its enterprise asset. There are three states in which data is vulnerable to threats from outside: during execution where it resides in a process memory, in-flight (during its transmission from a source to a destination), and at rest (where it is stored).
As the data is collected from different sources in various forms, good analytics tools and technologies provide the agility required to react almost in real-time. The data have to be monitored, the collected data analyzed, any anomalies or suspicious behaviors identified and action has to be taken to prevent a security breach. If a security breach occurs, we must take various forensic actions involving data analysis from multiple sources.
A good business analytics master’s program provides a wide selection of business analytics classes and a disciplined process to using multiple subjects to develop enough mastery to start a career.
At my company, C3DNA, we use data analysis to auto-scale workloads in data center or cloud environments to meet large fluctuations in user demand — or changes in resources on which the applications are executed. We make any application run on any cloud without having to change the application, the operating system in which it executes, or the infrastructure (server, network, and storage) provisioning processes. This gives the enterprises a choice to use their data centers or any cloud from any provider on demand.
By making applications self-aware and self-managing (using a cognitive overlay just as biological systems do), we reduce the complexity of application management in a distributed network of clouds and save operational costs by an order of magnitude. The cognitive overlay allows us to provide highly available systems even on a not so reliable infrastructure.
Tell us about the Business Analytics Security course you teach at GGU? The Business Analytics Security class is part of the Business Analytics master’s degree program and is designed to help both IT professionals and data analysts to understand how analytics assist in proactively manage information security. In a globally connected computing infrastructure, communication, collaboration, and commerce (at almost the speed of light) are demanding real-time management of information confidentiality, integrity, and availability.
If a security breach occurs, we must take various forensic actions involving data analysis from multiple sources.
Why is graduate-level work important for a business analytics career?
Data analyst or scientist careers demand expertise in multiple disciplines: probability and statistics, data exploration and visualization technologies; data ingestion, cleansing, and transformation technologies; introduction to machine learning and various tools and algorithms; and familiarity with tools such as R, Python, and Machine Learning A good master’s program provides a wide selection of business analytics classes and a disciplined process to using multiple subjects to develop enough mastery to start a career.
Golden Gate University is proud to have Rich Clayton as a member of the Advisory Board of the new Master of Business Analytics program. He is the VP of Oracle’s Business Analytics Product Group and is responsible for the global adoption of the company’s Business Intelligence, Big Data Analytics, and Enterprise Performance Management solutions.
Clayton’s passion for helping companies create value from data is evident in this brief video (1:24) about GGU’s Master of Science in Business Analytics program. The program, he says, has been “designed by business professionals, taught by business professionals, for business professionals,” making it unique and highly relevant to the demands about this rapidly growing profession.
If you are considering a career in Business Analytics and are a database query geek, there are many free sources of data on the Internet to play with. Here are 10 examples from the mundane – grain and construction — to the entertaining– baseball and hip-hop lyrics.
Mentions of Donald Trump in the hip-hop data trove were 160 positive (mentions of his wealth dominate), 74 neutral, and 34 negative.
If you want to hunt for your own data to play with, GGU Adjunct Professor Rao Mikkilineni suggests this list of 25 websites for data science projects which contain the sources above. Mikkilineni currently teaches courses in GGU’s master’s degree in Business Analytics program.
If you are considering a career in business analytics, a working knowledge of Hadoop – a platform for handling Big Data – goes a long way. Hadoop is in wide use around the world and in the San Francisco Bay Area, where the demand for business analytics professionals is the highest (according to Forbes).
Big Data has transformed businesses and requires a new class of data intelligence professionals that can meet the challenge interpreting it. But there are also technical challenges to working with Big Data. Organizations ingest an enormous amount of data every millisecond—most of which is unstructured and cannot be handled by conventional databases. The servers needed to “crunch” these data are expensive and can be difficult to implement. Among the solutions to these challenges is Hadoop, an open source framework that uses a variety of tools and techniques to peer into big data and give decision-makers better insight. Hadoop is a component of the curriculum of Golden Gate University’s new master’s degree in Business Analytics because it is geared toward Big Data and provides a resource to professionals who specialize in its interpretation.
We asked GGU alumnus and Senior Hadoop Administrator at UnitedHealth Group, Ken Nakagawa, to answer a few questions about Hadoop.
How would you explain what Hadoop is if someone asked you at a bus stop or on Caltrain?
Hadoop is free open source software that allows companies to store and analyze data that was probably not utilized before because of the cost of hosting many proprietary servers, as well as the processing speed needed to examine large data sets.
The longer answer is that Hadoop has the significant advantage of being able to analyze unstructured data like log files, chat conversations, and tweets, etc. The amount of data generated is so enormous that conventional large computer systems and relational databases cannot keep up and provide a cost-efficient solution. A significant advantage is that Hadoop is open source and you can use commodity servers. Before companies such as IBM, HP, Sun Microsystems, etc. would offer data warehouse products for storing a large amount of data, but they were usually very expensive.
What method does Hadoop use to make data crunching faster?
Our Hadoop cluster has about 370 nodes (servers) the combined storage is about three petabytes. At my company, we are ingesting between 9 and 12 terabytes of data a day. Hadoop can make data crunching faster by combing a set of commodity PC servers a cluster can act like one giant computer. Hadoop will assign a part of a job to each server within the cluster to work on their part, get their results, combine them and present the results as a whole. Clustering nodes – rather than buying a large server – provides scalability depending on your need. You can easily scale from three nodes up to thousands. It is both technically efficient and cost effective.
I think a Business Analytics specialist will have an advantage if they study or have experience with Hadoop and its analytic tools. If business people can get hands on experience accessing all that data, they usually find new information and patterns.
Can you describe a particular project that Hadoop that was memorable?
EBay is a big Hadoop user. All those items you see for sale on their site are stored as unstructured data in a Hadoop database. When I was a consultant, EBay was one of my most memorable customers because their business is so integrated with Hadoop.
How does Hadoop make sense of unstructured data?
Hadoop can store unstructured data and have databases like Apache HBase™ serve it up. You can store, query and even modify the data just like using a relational database and retrieve it just as quickly.
Why would a business person need hands on knowledge of Hadoop – outside of the technical side which you inhabit?
I think a Business Analytics specialist will have an advantage if they study or have experience with Hadoop and its analytic tools. If business people can get hands on experience accessing all that data, they usually find new information and patterns. For a big company, it can give you access to other department’s data that you didn’t have before. You will have a greater source of data to work with!
Ken Nakagawa (MS ’02, Database Development and Administration) is the Senior Security Consultant Hadoop Administrator at UnitedHealth Group.
Dr. Gordon Swartz is the Dean of GGU’s Edward S. Ageno School of Business
“Big Data” is a catch-all term to describe all manner of information and decision-making challenges faced by business, government, and nonprofit organizations. The development of modern computing and communications systems has driven a decades-long information explosion culminating in an age where billions of people carry a personal ‘supercomputer’ with them wherever they go – their mobile phone. We have instant access to countless information sources and can connect to and share information with billions of others in many ways — text, voice, video, or social media. Big Data is one way of simplifying – or oversimplifying – the fact that the volume of data, the variety of data, and the velocity of data is growing exponentially.
Some of our world’s billions of data streams contain incredibly valuable insights – or signals – that we can use to improve our organization’s performance, better serve our customers or stakeholders, and compete effectively in today’s data-driven marketplaces. To make astute business decisions, we must continuously enhance our analytics capabilities. Any business can benefit from a Business Analytics professional.
Business analytics capabilities are so fundamental, so critical to effective business decision making, that forward-thinking organizations are making significant investments in people and technologies to remain competitive. We’re now seeing a tremendous demand for analysts, managers, and leaders with business analytics capabilities.
Who benefits from a business analytics expertise? Any analyst, manager, or leader in an organization that currently relies or will rely on insights from Big Data – In other words, just about everyone. Big data touches nearly every discipline including IT, Security, Human Resources, Operations and Logistics, and Marketing, to name a few. So, while these examples might add some tangibility, they miss the vast potential for the broad, strategic impact of Business Analytics.
Business analytics capabilities are so fundamental, so critical to effective business decision making, that forward-thinking organizations are making significant investments in people and technologies to remain competitive. We’re now seeing a tremendous demand for analysts, managers, and leaders with business analytics savvy.
A widely cited McKinsey white paper forecasted that by 2018 there will be a shortage of 1.5 million managers and analysts with analytics skills, as well as a shortage of 140 to 190 thousand employees with “deep analytical skills.” Specifically, data scientists are the highest paid among business analytics professionals who can write their own salary ticket.
To help meet the growing demand for Big Data skills, Golden Gate University recently launched a Master of Science in Business Analytics (MSBA) program to give business managers and leaders the capabilities to incorporate leading-edge business analytics ideas and tools into their strategic planning. These skills also allow managers to design and implement Big Data and analytics initiatives that drive business value and help those firms build a competitive advantage. The MSBA is not an academic-focused program, but one that ensures that business managers and leaders have the Big Data and business analytics capabilities to lead their organizations effectively and to get the greatest benefit from their data.
About Dr. Gordon Swartz
Dr. Gordon Swartz holds a Doctor of Business Administration degree from Harvard University, a High Technology MBA from Northeastern University and bachelor degrees in nuclear engineering and political science from MIT. His articles and case studies have been published in distinguished academic journals, including the Journal of Service Research, Sloan Management Review, Marketing Management and the Harvard Business Review. As vice president of MarketBridge, Inc., he led major marketing, sales strategy and transformation efforts for Fortune Global 500 companies.
Arshad Khan, M.E, MBA, is an IT professional with expertise in business intelligence built over a 30-year career. He will be teaching Data Visualization and Storytelling as part of Golden Gate University’s new master’s degree program in Business Analytics.
What are big data and data analytics?
Big Data refers to datasets or combination of datasets whose size and complexity is beyond the ability of conventional technologies and tools, such as relational databases, to capture, store, manage, and analyze within the time necessary to make them useful. Data Analytics is the collection of disciplines that use data for providing insight and helping make better decisions.
Why do business analytics skills matter?
People with analytics skills provide organizations with valuable and timely information that they can use to improve products, manage costs, and increase revenue. No organization can expect to compete or operate efficiently unless they understand what their data says.
If anyone wants to ride the wave of a growing field where there will be numerous high paying jobs for the foreseeable future, getting a degree in analytics will help them.
Can you describe a business analytics project that you have been involved with?
At Juniper Networks, I led a development effort that involved merging data from two independent systems to produce a flexible report which enabled us to analyze how we were doing against our competitors (such as Cisco, HP, and others) using various criteria (such as deal size, product family, geography, etc.). Without the ability to analyze data that was scattered, we were running blind.
What is your current job?
The company I work for, Modemetric, has developed a Business Intelligence analytics product that we think addresses a need in the market for a robust, secure, and flexible tool. Its Lantern product enables a self-service model in which non-technical people can create sophisticated reports.
Adjunct Professor Arshad Khan works at Modmetric, a company
that provides a Business Intelligence tool known as Lantern
What do you teach in the Master of Science in Business Analytics program at GGU?
Data Visualization and Storytelling is a class I teach where students will learn various aspects of data visualization—from theory to practice. They will also be introduced to a data visualization tool, which will be used for developing a project that will be assigned in this class.
What can you say about a business analytics career?
Data generation is increasing exponentially. If anyone wants to ride the wave in a growing field where there will be numerous high paying jobs for the foreseeable future, getting a degree in analytics will help them. There is currently a big shortage of analytics professionals, and this shortage is going to get worse in the foreseeable future. Data scientists are often the highest paid professionals at a company and can write their own salary ticket these days. Business analysts and analytics pros are among the most highly sought professionals. Go to Glassdoor and do a search for business analytics and you will see the latest salary ranges in the San Francisco Bay Area.
Arshad Khan, M.E, MBA, is an IT professional with expertise in business intelligence built over a 30-year career. He will be teaching Data Visualization and Storytelling as part of GGU’s new master’s degree program in Business Analytics. Here is his list of great visualizations from popular business analytics dashboards.
New York Taxis Data Visualization (Tableau)
Visualizing a huge set of information about the country’s biggest taxi market. Make sure to click on the data points.