You're navigating a Business Architecture interview. How do you showcase your data analysis expertise?

La aquitectura empresarial es un pilar fundamental de la organizacion empresarial sobre la que descansan procesos y la forma de relacionarse con el mercado. Solo desde una BA pensada para ello se puede entender la digitalizacion de las empresas y desde ahi la forma de incorporar las tecnologías basadas en la lógica de los datos tanto propios como externos , para conseguir avances incrementales , que mejoren la productividad y de sentido a crecimientos sostenibles en el tiempo.

Enterprise architecture is a fundamental pillar of the business organization on which processes and the way of interacting with the market rest. Only from an EA designed for this purpose can the digitalization of companies be understood, and from there, the way to incorporate technologies based on the logic of both internal and external data, to achieve incremental advances that improve productivity and give meaning to sustainable growth over time.

Having complete data accessible from a consolidated source is important for making informed buisiness decisions. The architecture should be set up so this is possible and sustainably so that little to no manual data manipulation must be done to gain a full understanding of the data present.

Tools might have limitations hence would recommend to do analysis using excel and Lookups along with sql , python etc to hash out variations clearly.

Las herramientas de datos , han sufrido a lo largo del tiempo la misma evolucion que la misma utilizacion de los datos en el desarrollo de las empresas : Desde los lenguajes de programacion a las utilidades asistidas por alguna variante de la inteligencia artificial , el recorrido por tipos de ,bases de datos , herramientas de visualizacion y utilidades específicas como las redes sociales , han transformado la forma de relacionarse con los datos y crecer en torno a ellos , no solo los propios sino tambien los del resto el mercado a nuestra disposicion

El pensamiento analítico está en la base de la toma de decisiones de cualquier entidad que tenga vocación de ofrecer algún tipo de mejora y crecer en torno a esa ventaja competitiva. Precisamente la digitalizacion y su exponente último , la inteligencia artificial son derivadas extraídas de un proceso evolutivo sin par alrededor del pensamiento analítico que ha diseccionado hasta el más mínimo la detalle la forma óptima de tomar decisiones , en entornos con conocimiento imperfecto por parte de los elementos decisores , explotando una forma de pensamiento que viene disciplinas como la teoría de juegos y la teoría de la decision de Nash y Von Newman

Analytical thinking is at the core of decision-making for any entity that aims to offer some kind of improvement and grow around that competitive advantage. Precisely, digitalization and its ultimate exponent, artificial intelligence, are derivatives extracted from an unparalleled evolutionary process around analytical thinking, which has dissected to the smallest detail the optimal way to make decisions in environments with imperfect knowledge on the part of decision-makers, exploiting a way of thinking that comes from disciplines such as game theory and the decision theory of Nash and Von Neumann.

Your analytical and technical skills are important, of course, but they aren't your ace card. The biggest asset you bring to an organization is a sincere desire to understand how it operates and what its leaders care about. While interviewing this is expressed in two ways, research and curiosity. Regarding "research", it's great you learned things in school or at your last gig. Put all that in your pocket for sometime after you're hired. Before your interview, find out all that a human can find out about this particular business. History, market position, press releases, everything. On "curiosity", take every opportunity during your interview to shut up. Listen intently. When you do open your mouth, ask a thoughtful, probing question.

Effectively showcasing your data analysis expertise can set you apart. Use case studies framed within the Challenge-Approach-Outcome structure to achieve this. Start by explaining the business problem, then describe the data analysis methods and tools you applied, emphasising any innovative approaches. Conclude by illustrating the positive outcomes, particularly how leveraging data created new revenue opportunities or resulted in substantial cost savings.