Describe what your organization does, and how it relates to data science.
AE Business Solutions is an IT Systems integration and consulting firm that has been an industry leader in the Midwest market for nearly 75 years. With a value-driven, client-first approach to all of our integration and service solutions, AE prides itself on delivering emerging technology solutions through our meticulously vetted portfolio of products and our expertly certified engineers, architects, and data scientists. While AE has many Centers of Excellence across Security, Infrastructure, Cloud and DevOps, and Talent Acquisition, AE’s Data Intelligence Center of Excellence gives us a unique market perspective in how best to help clients begin, grow, mature, and modernize their analytics capabilities. Our Data Science and Data Architect team members have worked with a spectrum of organizations in the Midwest, from mid-market to large enterprise, helping to assess, implement, refine, and realize their data science and analytic goals.
Why is sponsoring the Research Bazaar important to you?
At AE we say, “Innovation is in our DNA.” and part of what sets AE apart from other IT systems integration and consulting firms is our commitment to providing and facilitating thought leadership and giving back to the communities we service in any ways we can. We host many of our own technology events that seek to bring together IT innovators and thought leaders across many different fields and sponsoring the Research Bazaar is yet another opportunity for AE to further pollinate the innovation DNA that is the hallmark of our identity and the reason for our continued success. We believe that having these sorts of innovative industry opportunities is critical in the continued growth of the IT world, locally and globally, and AE will always want to help to further that conversation however we can.
In what ways do you see data science actively shaping and influencing real-world outcomes within your field or industry?
As a consulting firm, we work with a wide range of industries and see many different applications of data science. The biggest impact we see is organizations adopting and integrating predictive models into their daily operations and decision making. The demand for predictive models is greater than ever, and our challenge is in helping organizations to develop and support them. This demand has led organizations to adopt common use cases, such as predicting sales or member attrition. Industry verticals ranging from public education to large-scale manufacturing can all benefit from predicting operational outcomes or understanding preferences about their constituents though data science.
An equally important aspect of adopting predictive models is an improved data environment that must be built to support them. In addition to more common use cases, organizations have also developed more bespoke solutions, where we see applications of algorithms which create unique business opportunities and new revenue streams. To support a diverse set of models, data teams are investing resources in communicating and operationalizing these machine learning systems. We see a large migration to cloud (as opposed to on-premises) platforms. Cloud platforms can provide compute power, continuous integration, and storage capabilities which promote a robust data science environment.
Beyond the accompanying infrastructure, implementing predictive models requires thorough understanding between data teams and business users. Data science is a new and intricate discipline, and business users have an increased responsibility to communicate business needs to data team members. Likewise, data teams must be prepared to communicate their ideas and results to business users in an effective manner. In our experience, we take on a didactic role as data scientists, explaining different modelling techniques and their limitations. This has allowed us to bridge the gap between business knowledge and data science within many organizations.
Ultimately, we see data science shaping our partner organizations into more capable versions of themselves, armed with new methods for learning from data and robust data systems to take on new challenges.
In what ways does your organization encourage collaboration and knowledge sharing to maximize the impact of data across different departments or teams?
What falls under the umbrella of data intelligence – data engineering, data science, the various “ops” – is an interdisciplinary and often blurry “combobulation” of professions. For example, a definitive task of a data scientist is to train and validate machine learning models. But it’s evident that the quality of the input data impacts model performance and scope; hence the phrase “garbage in, garbage out.” Additionally, after training is complete, there are questions around deployment: Where do we put the model? How do we retrain it on new data? What happens before and after training a model is no less important to a data scientist than the training itself. However, because a data scientist’s work is highly specialized, these responsibilities may be delegated to other data team members: a data engineer could ensure quality data, and a DevOps engineer could ensure copacetic operations post initial training.
Specific to our organization, we realize many skills needed to complement and make actionable a data scientist’s valuable work are found in other professions, particularly from Cloud and DevOps. There are many analogous operations between maintaining a software application and deploying a machine learning model. So, by combining data science knowledge with DevOps skills, we get (yet another) operations engineering field dubbed “MLOps”. We can achieve this combination of knowledge and skills via project collaboration, and discussion of new data products coming to market.
Can you share a success story where your organization’s data science efforts had a positive impact on a broader community?
AE Business Solutions’ charity foundation, AE Cares, is committed to serving the community by supporting veterans, improving racial equality, and much more. And as an IT consulting firm, we’re in a unique position to help others achieve success in the modern, technologically driven workplace. We’ve partnered directly with organizations, such as i.c. Stars and Maydm, to promote professional development in data science and IT.
Employees from AE Business Solutions regularly collaborate with i.c. Stars to discuss their career and education, review resumes, and provide expert insight to the young professionals participating in the program. What we enjoy most about volunteering with i.c. Stars is learning about the diverse backgrounds of each participant. This leads to a discussion about how to convey their unique experiences, leverage their business knowledge, and improve their skills as a young professional about to enter the field.
AE Business Solutions also collaborates with Maydm, a non-profit organization dedicated to teach more women and minorities STEM skills to enable them for successful careers in technology and science. AE works with Maydm to enable their internal analytics efforts and works regularly with the organization on various initiatives.
AE Cares proudly continues to contribute to the education of young professionals because we understand it is our shared responsibility to make our broader community an equitable and uplifting place to live. Partnering with organizations like i.c. Stars and Maydm allows us to contribute to this goal the way we know best: guiding others with our expertise in technology.