Business intelligence (BI) is a valuable skill that can help you analyze data, generate insights, and support decision-making in various domains. However, landing a BI job can be challenging, as you need to demonstrate your technical, analytical, and business acumen in an interview. To prepare for a BI interview, you should research the following aspects:
Before you apply for a BI position, you should learn as much as you can about the company and its goals. What is the company's mission, vision, and values? What are its main products, services, and customers? What are its current challenges and opportunities? How does it use BI to achieve its objectives? By researching these questions, you can show your interest, fit, and alignment with the company and its culture.
Generative AI | Analista de Dados | Ciência de Dados | Mentor em Dados | Professor | MTAC
Sim, é fundamental que o candidato pesquise sobre a empresa, quais seus clientes, qual o ramo que atua, é consultoria ou é empresa única... Veja a reputa??o dela e o que funcionários e ex-funcionários comentam, tem sites específicos para isso... E claro, veja se os objetivos da empresa se encaixam com os seus (as vezes n?o temos essa op??o, eu sei! Mas é uma dica kkk)
1. Look at the company's site, understand what they do. 2. Research the industry and find the main competitors, see what they do. Are the companies similar in scope? Do they serve the same markets? 3. What data would make sense for the company to gather in the course of their operations at the bare minimum? This is what you're likely to be working with.
Preparing for a business intelligence (BI) interview involves researching various aspects to showcase your knowledge, skills, and understanding of the field. Here are key areas to focus on: Company Background: Job Role and Responsibilities: BI Tools and Technologies: Company's Data Environment: Industry Trends and Challenges: Company's BI Initiatives: Data Governance and Security: Competitors: Common BI Interview Questions: Data Visualization Best Practices: Data Modeling Concepts: SQL Proficiency: Cloud BI Solutions: Your Achievements and Projects: Behavioral Questions: Questions for the Interviewers: Certifications and Training: Industry Certifications:
Another important aspect to research is the role and its responsibilities. What are the specific skills, tools, and knowledge that the role requires? What are the main tasks, projects, and deliverables that the role involves? What are the expectations, metrics, and goals that the role follows? How does the role collaborate with other teams and stakeholders? By researching these questions, you can highlight your qualifications, experience, and achievements that match the role and its requirements.
Generative AI | Analista de Dados | Ciência de Dados | Mentor em Dados | Professor | MTAC
Muito importante este ponto, seja sincero com você mesmo e jamais fale que sabe algo que n?o sabe! N?o vá lá e olhe o que a vaga pede, coloca no chatgpt pra ver o que é, e chega dizendo que sabe... isso é muito ruim para você mesmo em um futuro bem próximo! Normalmente indico se tem uns 60 a 70% do solicitado, já vale se candidatar e conversar! Mas sempre, sendo claro e sincero!
Your goal is to deliver value through increased knowledge using tools that minimize costs compared to what the company is using. A lot of the knowledge transfers between tools, so I would focus more on aspects like domain knowledge and how to collaborate with other teams to make sure that the intelligence you're going to produce is useful to them. Too many reports end up unused because they are not built with the audience in mind.
A third aspect to research is the interviewer and their background. Who are you going to meet and talk to in the interview? What are their roles, titles, and responsibilities in the company? What are their professional backgrounds, interests, and expertise? How can you connect with them on a personal and professional level? By researching these questions, you can build rapport, trust, and credibility with the interviewer and tailor your answers to their perspective and expectations.
Generative AI | Analista de Dados | Ciência de Dados | Mentor em Dados | Professor | MTAC
Importante saber um pouco de quem vai conversar com você, até pra dar uma olhada como é a pessoa, o que estudou, o que gosta de compartilhar, quanto tempo e jornada dentro da empresa e etc! é legal até perguntar algo ao entrevistador com base nesta pesquisa... gera engajamento.
Don't be too technical with a non-technical interviewer, of course, but take a few minutes to assess the technical interviewers as well. I would ask them to describe the technical requirements of the position and you can then describe how you would fit into the position. If you're given a name beforehand, do a little research. Doing your homework is always recommended.
A fourth aspect to research is the industry and its trends. What are the current and emerging trends, issues, and opportunities in the industry that the company operates in? How does the company position itself in the industry and differentiate itself from its competitors? How does BI support the industry's growth, innovation, and transformation? By researching these questions, you can demonstrate your awareness, curiosity, and enthusiasm for the industry and its potential.
Generative AI | Analista de Dados | Ciência de Dados | Mentor em Dados | Professor | MTAC
Ponto muito importante, é legal já chegar com um entendimento da área daquela empresa, qual o ramo de atua??o, dá uma estudada já em indicadores relacionados e melhores práticas por exemplo... vai que falam algum termo mais do negócio, pode ser que vc tenha passado mesmo que brevemente por cima e lembre de algo... Hoje em dia, eu daria uma dica de chegar comentando com Generative AI poderia apoiar naquela área de atua??o... #ficaadica
At the interview you're the outsider and you can offer them a fresh view of their business, unburdened by inside information and company culture. Tread carefully, but if you can give them valuable suggestions, they'll appreciate you for being insightful.
A fifth aspect to research is the data and its sources. What are the types, formats, and sources of data that the company collects, analyzes, and uses? How does the company ensure the quality, security, and governance of its data? What are the data models, schemas, and structures that the company employs? How does the company integrate, transform, and store its data? By researching these questions, you can showcase your technical, analytical, and data literacy skills and knowledge.
Generative AI | Analista de Dados | Ciência de Dados | Mentor em Dados | Professor | MTAC
Você n?o tá ali só para responder, você pode perguntar... e uma coisa que acho válido perguntar s?o sobre as origens de dados daquela empresa! como é o dia a dia, seguran?a de dados e etc! Já pensou se a empresa só usa excel kkk (brincadeira)! Cada ferramenta é importante e se tá lá, é porque é a melhor para se utilizar naquele momento e naquele cenário!
A sixth aspect to research is the tools and their functions. What are the tools, platforms, and frameworks that the company uses for BI purposes? How do they enable data extraction, manipulation, visualization, and reporting? What are the features, functions, and benefits of each tool? How proficient are you in using each tool? By researching these questions, you can display your practical, hands-on, and problem-solving skills and abilities.