How Data Analytics Can Transform IT Operations
Imagine you’re driving home from the airport at 11 p.m. Suddenly your car breaks down. You dial AAA, but after several attempts, the only sound you hear is a busy signal. Frustrating, right? Thanks to IT Director Frank D’Arrigo and Splunk Cloud, the odds that you’re left stranded have now been greatly reduced.
Pre-Splunk, D’Arrigo had no way of knowing how congested each AAA phone circuit was at a specific point in time. Splunk, which is “like a search engine for machine data,” allows you to connect IT data sets together to tell a full story. For example, if someone swiped into an office building with their employee badge at 3 a.m., the scanner would collect that data. The office security camera also collects data that allows you to confirm the late-night arrival’s identity – or reveal that they were using another person’s employee badge. “Normally, data from a badge swipe and data from a security camera wouldn’t be compatible, but Splunk allows you to tie them together,” D’Arrigo says. “It allows you to see patterns you never would have known existed.”
"We now have other departments contacting us to decipher patterns..."
Frank D’Arrigo, IT Director, AAA Western,
AAA Central New York
Initially, AAA planned to use Splunk exclusively to help with security. But D’Arrigo soon began to realize the software’s potential broad-reaching benefits – and applied it to the company’s phone systems. Before, “When I got a busy signal, I had no way of knowing how busy the specific phone circuit was,” he says. “Now I’m able to tell if one circuit is 60% busy, while another is 30% busy, and so forth – Splunk connects all the phone systems, and automatically reroutes calls to a line that is less busy.” Thanks to Splunk’s connective feature, AAA ended up with self-monitoring, self-diagnostic, self-healing phone systems – and the ability to reduce the chance of phone circuits becoming 100% busy, so customers are less likely to receive a busy signal.
AAA is enjoying seemingly endless applications of the software. “We now have other departments contacting us to decipher patterns,” D’Arrigo says. “Facilities asked, ‘What can you tell us about the environmentals when we’re not here?’ Well, we found that the building management system that controls lights was turning off and on multiple times per night. We told facilities and they were able to fix this, saving on electrical costs.”
Splunk has effectively helped D’Arrigo and AAA identify and prevent threats from turning into problems. “We understand our operating environment better than ever. It’s addressed the old adage, ‘You can’t fix what you can’t see.’ Now we can see what’s happening when it happens (and in many cases, predict what’s going to happen), and fix it.”
Frank D’Arrigo is the IT Director at AAA Western and Central New York. He is also a member of the Splunk Cloud Council.
The Data Science Certificate v. Master’s Degree: How to Make the Right Choice for Your Career
If you’re wondering how to take the next step professionally, or beginning to consider a career in data science, odds are you have contemplated continuing education. With the explosion of the data science field, a number of programs have emerged to meet the needs of prospective students and employers.
For those searching, however, the variety of available programs and formats is a double-edged sword – and can leave potential students mulling the difference between a MOOC and a master’s. “Would I develop the depth of skill required to be successful through a certificate?” “Is it worth it to invest more time and money in a master’s program?” Ultimately it depends on the individual’s specific needs, but there are a few differentiators between the two program formats.
The first difference is depth. According to Daniel Conway, director for the Center for Business Analytics and the MBA in Analytics at Loras College, “A certificate is generally five graduate courses (but doesn’t need to be), and a master’s is 12-15 classes.” While no single master’s program could cover all the disciplines involved in data science in significant depth for one to establish expertise in each area, students are likely to delve deeper into the subject area – which is why master’s programs are popular among those looking to switch careers. For newcomers to the data science field, completing a master’s program can provide much-needed experience working with unstructured data, and the mathematical and computational depth to be an attractive candidate to prospective employers.
"A strong program will enhance higher order processing skills... as well as look at the 'big picture'..."
Uma Gupta, Professor of Business, State University of New York at Buffalo State
A master’s program may also be a good fit for students aiming to reach the next level in their careers. “A strong program will enhance higher order processing skills such as the ability to handle chaos, complexity, and uncertainty, as well as look at the ‘big picture,’” says Uma Gupta, professor of business at the State University of New York at Buffalo State. “It will lead you to ask, ‘What are the other ways to solve this problem?’” Besides the deep learning that takes place in each course, peer interaction (whether online or offline) is an important component of a master’s program. According to Gupta, “It’s not just the textbook or readings – there is a lot of individual learning that takes place among your cohort, and helps with the ability to think deeply and in complex ways.”
The certificate is better suited to those looking to gain a specific skill set – or a quick overview of the field. For someone with an existing knowledge base who is looking to gain expertise in one area, Gupta recommends the six- or eight-week certificate program. “It can be very tailored. For example, you could pursue a certificate in Hadoop or another programming language for a very thin slice of the field,” she says. “There are also programs that offer a quick, broad overview.” Self-paced programs are available, and often classes can be taken in any order, whereas master’s programs typically contain sequence-dependent courses.
Practical. Functional. Results-Driven.
Saint Mary’s College M.S. Data Science
At Saint Mary’s, you’ll have the opportunity to engage in a real-world practicum that involves developing data analysis tools and applying them to a pressing need at an organization. Whether designing a database, cleaning and analyzing a dataset, or developing a predictive model, you will gain valuable insight into the organization’s operations and objectives. “Our graduates will be prepared to enter into the data analysis process at any stage, from the initial formulation of the question to visualizing data to interpreting the results and drawing conclusions,” said Kristin Kuter, program director. “As a result, they’ll be more versatile practitioners, whether it’s for their own start-up, an employer, or a client.”
For Mike Durham, a Saint Mary’s student and solution architect with the Teradata Corporation, the increased analytics skills have significantly elevated his ability to find and interpret meaningful data patterns - and he’s only just finished year one of the program. “I’m able to dig beyond what a simple analyst can do, and not only tell them what happened, but why it happened, and why we came up with the answers we did.”
"I’m able to dig beyond what a simple analyst can do, and not only tell them what happened, but why it happened..."
Mike Durham, Saint Mary’s student and Solution Architect, Teradata Corporation
Durham’s newly enhanced skill set is a major value-add for his employer, as he is frequently called upon to perform analytics for customers. “I’ve been able to quickly transition the materials I’ve learned in any particular class and immediately apply it to my job function. I now have discussions with the client’s data scientists on a peer-to-peer level, instead of just talking to them as a sales rep to a client,” Durham says.
For his practicum, Durham chose to do a proof of concept for Wright-Patterson Air Force Base. “They’re data-rich but information-poor at times,” he said. “So we were asked to analyze their maintenance data to discover any patterns that could enhance mission capability of the B1 bomber, C5, C17 cardinal plane, and F15 fighter jet.” The analytic techniques Durham employed can be applied to other industries, and he is presenting his findings at a worldwide conference.
Hear about Durham’s practicum, and how he performed path analytics to search for patterns in the maintenance data that could affect the planes’ ability to fly:
Want to take your career to the next level, like Durham?
Want to Be a Data Scientist?
Increase Your Fluid Intelligence
The data scientist’s biggest superpower is the ability to extract meaningful insights from raw information. How do they do this on a regular basis? The secret mainly lies with levels of fluid intelligence, or “the ability to think logically and solve problems in novel situations, independent of acquired knowledge,” says Uma Gupta, professor of business at the State University of New York at Buffalo State. “It involves identifying patterns and relationships that underpin novel problems and extrapolating these findings using logic.”
A simple way to activate fluid intelligence is to read something outside your discipline, or listen to music from a different genre. According to Gupta, “This strains your brain, makes it think and observe things it normally would not, and that comprehension is what leads to insight in your field.” Fortunately, the brain is your ally when it comes to increasing fluid intelligence; every day, it actively searches for opportunities to do things differently. When presented with an unfamiliar problem, the brain has to fasten the different pieces together, which stretches its capabilities. “When you travel and have to take the subway, you’re being challenged, because this subway system could be very different from yours,” Gupta says. “If your head hurts and you’re feeling burned out, that’s actually a very good sign. You want to tax your brain on a regular basis, as this triggers connections in brain cells.”
"If your head hurts and you’re feeling burned out, that’s actually a very good sign."
Uma Gupta, Professor of Business, State University of New York at Buffalo State
Challenging your brain by looking at things through a different lens leads to strong insights. “This is the reason fluid intelligence plays such an important role in data science,” Gupta says. “The reason companies hire data scientists is to generate insights that can help them gain a competitive advantage in their field. You cannot generate insights by simply looking at the world the same way you always have, which is why companies frequently hire consultants from different industries to help solve their problems.”
Continually training your brain by switching things up will increase your fluid intelligence, allowing you to harness the power of insight. “If you do the same thing every day, the brain pathways become jaded and dull,” Gupta says. “Challenge yourself to do something in a new way, whether it’s taking a new route to work or wearing your watch on a different wrist.” You never know what might spark your next insight.