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What are the best strategies for acing a data warehousing job interview?

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Data warehousing is a highly sought-after skill in the data-driven world of today. It involves designing, building, and maintaining databases that store and analyze large amounts of data from various sources. If you are applying for a data warehousing job, you need to prepare yourself for the interview process and showcase your knowledge, experience, and problem-solving skills. Here are some of the best strategies for acing a data warehousing job interview.

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Anand Jain

MTS at Salesforce | Data Engineer | Python | SQL | 2X Snowflake Certified | Matillion | Airflow
Mohammed Haris khan

Data Engineer at GlobalLogic

1 Know the basics

Before you go to the interview, make sure you review the fundamental concepts and terminology of data warehousing. You should be able to explain what a data warehouse is, how it differs from a data lake or a data mart, what are the benefits and challenges of data warehousing, and what are the main components and architectures of a data warehouse. You should also be familiar with the common data warehousing methodologies, such as the Kimball approach, the Inmon approach, and the Data Vault approach, and their pros and cons.

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Anand Jain

MTS at Salesforce | Data Engineer | Python | SQL | 2X Snowflake Certified | Matillion | Airflow
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For a beginner, having a complete end to end picture of data flow is good place to start. Source, storage and consumption layers. I recommend hands on along with reading to keep up the skills. Tools and concepts that helped me are 1. ETL : batch and CDC, SCD types 2. ETL Optimisations: building reusable elements. 3. Observability: Alerting and logging for auditing 4. Storage : cloud data warehouse, example snowflake. 5. Control tables driven automation. 6. Modelling : conceptual, logical and physical. Data vault, star and snowflake 7. optimisation (data retrieval): usage of materialised views, partitioning, clustering, and query optimisation. 8. SQL and python at your finger tips. Trust me queries and loops will save your time.

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Amritha Sanaka

Lead BI Analyst
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Before I go to the interview, I prepare all the concepts with an example to prove that I know what I am talking about. Ex: Snowflake , Star Schema , Kimball Approach. Its Advantages / Disadvantages/Performance Ques.. Whatever I know, I would always share real time examples which always add plus. I would be very confident in what I am answering. Writing SQL , ETL Skills etc.

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Arun Prakash S

IT Project Consultant
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Some of the basic technical part of Data Warehousing is understanding the 1.Difference between database and data warehouse 2.Knowledge in ETL tool (Informatica PowerCenter,Talend,Apache,Kafka,etc) with Reporting tools (Tableau,Power BIGoogle,Data Studio) 3. Understanding the Dimensions & Facts , Data modeling , OLAP & OLTP 4.How to do Performance Optimization

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Lidiane Nepomuceno Pecis

Microsoft Power BI Certified | Oracle BI Certified | ágil | Business Intelligence | Data Warehouse
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Conceitos como tipos de hierarquias, tipos de dimens?es e tipos de tabelas fatos, além de como se diferem e qual a diferen?a da abordagem na hora de realizar o processo de ETL em cada caso costumam ser pontos relevantes.

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Astitva Agarwal

Analytics Leader | Storyteller | Healthcare | Product
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Demonstrate a solid foundation in data warehousing concepts, including ETL processes, data modeling, and dimensional modeling. Showcase your understanding of key terms like star schema, snowflake schema, and OLAP to name a few. A basic foundation is what leads to successful careers and new skillset to be built upon, hence this should be the key focus.

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2 Show your skills

The interviewer will likely ask you to demonstrate your practical skills in data warehousing, such as designing a data model, writing SQL queries, implementing ETL (extract, transform, load) processes, and using data warehousing tools. You should be prepared to show your portfolio of previous projects, explain your design decisions and trade-offs, and write or debug code on the spot. You should also be able to use data visualization tools, such as Tableau or Power BI, to present and analyze the data in the warehouse.

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Mohammed Haris khan

Data Engineer at GlobalLogic
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In a data warehouse job interview, the interviewer will most probably ask you to design a data warehouse. Show your skills by designing a proper data warehouse by assuming and implementing the following: 1. Slowly Changing Dimension. Incorporate at least one SCD and explain implementation (type 1 2 or 3) 2. Conformed Dimensions. Properly create and explain Conformed Dimensions. 3. Include Date dimension and explain its importance in reporting to further show your deep understanding of data warehouse. 4. Draw a logical Data model to show star/snowflake schema using above dimensions and facts. 5. Finally write a SQL query to output the important KPIs from the data warehouse to emphasise on the practicality of your design.

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Claudio Bonel, M.Sc.

Professor e Pesquisador em Inteligência artificial | Cientista de dados e engenheiro de machine learning | Hardcore culture
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Mais que mostrar, "APRESENTE"! Só tome cuidado com o perfil do seu interlocutor. Se estiver apresentando para um/a profissional de RH, por exemplo, evite o "tecniquês", foco em apresentar como identifica desafios, como você é capaz de prover solu??es a esses desafios, organizando dados, gerando informa??es que prover?o conhecimento para tomada de decis?o. Siga uma linha mais de negócio. Se for alguém da área de dados, além de seguir a linha de negócio, pois continua sendo essencial, aproveite para apresentar como modelou seus dados, pq escolhe a técnica, ou seja, apresenta algumas habilidades técnicas tb. Dúvidas? Chamaí!

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Astitva Agarwal

Analytics Leader | Storyteller | Healthcare | Product
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Walk through practical examples of projects, emphasizing your problem-solving and analytical abilities. This can be done through various certifications or competition websites to have a meaningful portfolio. Moreover for experienced professionals I suggest showcasing major projects with 3 step approach - problem, complexity, solution to showcase the deep understanding and experience of the skillset.

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3 Know the trends

Data warehousing is not a static field. It is constantly evolving and adapting to new technologies and business needs. You should be aware of the current trends and innovations in data warehousing, such as cloud-based data warehouses, real-time data integration, data quality management, data governance, and data security. You should also be able to discuss how these trends affect the data warehousing landscape and what are the best practices and tools to leverage them.

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Sathiesh kumar M

Informatica | Data Model | Enterprise Architecture | Realtime integration | Webservices | App Modernization Multi domain MDM, C360 SaaS certified, Supplier 360, Reference 360, Product 360 cloud implementations
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Recent ?? trends see much development and moving away from traditional models and tools. More opensource formats for storage like parquet, arrow files and metadata layer like delta tables, icebergs that can be written and read by many number of ways. Need to keep up to the trend as this space is constantly evolving and your resume may look out of place in 5 yrs time quickly

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Claudio Bonel, M.Sc.

Professor e Pesquisador em Inteligência artificial | Cientista de dados e engenheiro de machine learning | Hardcore culture
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é até importante conhecer "Tendências", só toma cuidado com: 1 - é tendência mesmo ou é só uma roupagem nova, para algo que sempre esteve ali? Certifique-se antes. Dê uma pesquisada. 2 - Sendo uma tendência, você estudou? Já tem embasamento para falar sobre o assunto? Caso contrário, n?o toque no assunto. Evite se jogar aos le?es. Dúvidas? Chamaí!

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4 Ask questions

A data warehousing job interview is not only a chance for the interviewer to evaluate you, but also for you to learn more about the company and the role. You should ask relevant and insightful questions that show your interest and curiosity. For example, you can ask about the company's data sources, data strategy, data warehouse architecture, data analysis goals, data warehousing challenges, and data warehousing team structure. You can also ask about the expectations and responsibilities of the position, the work culture and environment, and the career development opportunities.

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Claudio Bonel, M.Sc.

Professor e Pesquisador em Inteligência artificial | Cientista de dados e engenheiro de machine learning | Hardcore culture
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Conhecer a Empresa para o qual você está realizando a entrevista é muito importante, pois vai demonstrar o seu interesse e saber mais sobre a mesma. Ent?o, antes da entrevista, fa?a o seu dever de casa, dê um pesquisada sobre a empresa, se possível localize os sócios, diretores, gestores no linked in, para dar uma olhada no currículo deles, o que já entregaram, onde trabalharam, o que pensam sobre a área de dados em geral. Esse tópico é importante, para lembrar que em uma entrevista, você também pode fazer perguntas. Ent?o, a partir do que pesquisou sobre a Empresa, fa?a algumas perguntas que seja interessantes, mostre que você está mais do que preparado! Dúvidas? Chamaí!

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5 Be confident

Last but not least, you should be confident in your abilities and personality. Data warehousing is a complex and demanding field that requires a combination of technical, analytical, and communication skills. You should be able to convey your passion and enthusiasm for data warehousing, as well as your willingness to learn and grow. You should also be able to handle feedback and criticism, and show your problem-solving and teamwork skills. Remember that the interviewer is looking for someone who can add value to the company and fit in the data warehousing team.

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Astitva Agarwal

Analytics Leader | Storyteller | Healthcare | Product
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Confidence is key. Clearly articulate your thoughts and experiences. Use the STAR (Situation, Task, Action, Result) method to illustrate your achievements. Maintain eye contact, and exhibit enthusiasm for the role and the potential contributions you can make to the team.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Astitva Agarwal

Analytics Leader | Storyteller | Healthcare | Product
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Understand the company's specific challenges and tailor your responses to highlight how your skills align with solving their problems. Showcase your adaptability and willingness to learn, emphasizing your ability to quickly grasp new technologies and methodologies. Additionally, demonstrate your understanding of the business impact of data warehousing, connecting technical aspects with organizational goals. Finally, prepare for scenario-based questions, illustrating your problem-solving approach in real-world situations.

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Lidiane Nepomuceno Pecis

Microsoft Power BI Certified | Oracle BI Certified | ágil | Business Intelligence | Data Warehouse
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Fale dos projetos que participou e como solucionou os desafios. Quais as metodologias e modelos foram utilizados e porque foram escolhidos em detrimento de outros.

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What are the best strategies for acing a data warehousing job interview?

1

2

3

4

5

6

1 Know the basics

2 Show your skills

3 Know the trends

4 Ask questions

5 Be confident

6 Here’s what else to consider

Data Warehousing

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What are the best strategies for acing a data warehousing job interview?

1

2

3

4

5

6

1 Know the basics

2 Show your skills

3 Know the trends

4 Ask questions

5 Be confident

6 Here’s what else to consider

Data Warehousing

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感谢您的反馈

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