You’re interested in data warehousing. What can you do to stay ahead of the curve?

Data warehousing is an an amazing competency that can help you revolutionize a business. The basics of data warehousing are found in modern data practices. Trying to build a current stack it's important to still understand the basic principles of data movement, data storage, and data modeling. While you might think of the current iteration of a modern stack relying on a a data lake house vs data warehouse, most advanced professionals will tell you both are relevant and in some enterprise both are a necessity. Depending on your companies data culture and data literacy it's sometimes best to drive a data warehouse concept to removed the technical competency required for a lake house structure.

In the realm of DataWarehouse to stay up to date: 1.Learn the Basics: Familiarize yourself with the fundamentals of data warehousing, ETL (Extract, Transform, Load) processes, and the role of ETL tools in managing data. 2. Gain Theoretical Knowledge: Study key concepts such as data modeling, data integration, and dimensional modeling. Online resources, tutorials, and courses can provide a solid theoretical foundation. 3. Hands-On Practice: Practice using the chosen ETL tool by working on small projects or sample datasets. Many tools offer free versions or trials for practice purposes.

To stay ahead of the curve in data warehousing, as a long years and cloud experienced data engineer, you can continuously improve your technical skills, keep up-to-date with the latest trends and technologies, stay connected with the community of data professionals, and stay focused on the business outcomes and value of data warehousing.

One needs to understand you need to master the core concepts and principles of data warehousing. These include data modeling, data integration, data quality, data governance, data security, and data architecture. Understand the different types of data warehouses, such as relational, dimensional, and cloud-based, and their dis advantages

Data warehousing is a way to centralize the business intelligence ecosystem by unifying data from diverse data silos. If done right it has the impact of changing the business into a data driven organization. Signs of data driven organization: Changing business processes to improve revenue, margin and process cost improvements. Creating new revenue streams and ecosystem opportunities. with the advent of cloud we have low cost of storage & decoupling of storage and processing. This enables organizations to save all their historical data and other data elements that can help drive the transformation.

Certainly look at Google Big Query (GBQ) technology when investigating and analysing large consumer data sets. This will provide many of the consumer analysis tools that Google is also using.

DW's have been modernizing. Cloud Storage: Leveraging Object stores like AWS S3, for raw data, before it is processed in RDBMS, for DW and the data marts. Real-time DW's: Newer data integration tools can transform and analyze data as it's created, providing insights "on the fly." Imagine tracking the business events to see what resonates with customers, with much delay. AI-powered Analysis: DW are getting smarter! AI can automatically find patterns and anomalies in data, helping uncover hidden trends and make data-driven decisions faster. Data Lakes & Lake Houses: Imagine a lake for all data (structured & messy) and a DW for the most important, organized info. Lake Houses are being used for best of both worlds.

Exploring new technology in data warehousing opens doors to exciting possibilities and enhanced efficiency. With the rapid pace of technological advancement, staying updated is essential to harness the latest tools and techniques for optimizing data management processes. By embracing innovations such as cloud-based data warehouses, advanced analytics, and artificial intelligence, organizations can unlock deeper insights, streamline operations, and gain a competitive edge in the market. Exploring new technology empowers data professionals to adapt to evolving demands, leverage emerging trends, and drive transformative changes that drive business growth and innovation.

Enabling online data streaming is essential for rapid decision making, Also adopting embedded analytics and generative AI would reduce the complexity of technology for end users.

Modern data warehousing goes beyond traditional setups, incorporating NoSQL databases like MongoDB for diverse data types, and big data frameworks like Hadoop / Spark for scalability. Tools such as Azure Synapse integrate analytics and data warehousing, Microsoft Fabric extends Fabric by including complex processing and Co-pilot, and Databricks provides a unified platform for big data and machine learning. These advancements signal a shift towards versatile, efficient, and cost-effective data solutions, enabling organizations to unlock their data's full potential in the digital age.

It might be pertinent to keep practicing classic architect skills - create data marts versus warehouse , snowflake versus star, understanding the heterogenous nature of the data and workflow etc. we need to balance fundamental with emergent platforms like Kaggle - where cross industry crowd sourced algorithms bring newer learnings.

I have started my career as an ETL developer Now I am working as a Bigdata developer.And applying the same concept in Spark as well to process the data as per the requirement. So we used to acquire new skills and technology as per the market trend.

Il y a plusieurs outils ou technologies open source. On peut trouver des ressources en ligne pour se former et pratiquer. Par exemple il y a une grande communauté autour du langage Python/ PySpark cela facilite son apprentissage car beaucoup de ressources sont disponibles en ligne. Par ailleurs Jupyter notebook est très adapté pour commencer à coder avec python. En fin on peut aussi s’abonner à des plateformes de formation telle que DataCamp ou coursera

Develop a continuous learning plan that includes regular practice sessions. Seek constructive feedback on your projects and code. Participate in data warehousing hackathons or coding competitions to challenge yourself with time-bound problem-solving.

To practice DWH and ETL skills online for free, utilize various platforms and resources: i) Online Courses: Access free courses on Coursera, edX, and Udemy, focusing on hands-on projects. ii) Interactive Websites: Use SQLZoo, Mode Analytics, and LeetCode for interactive SQL tutorials and exercises. iii) Free Tools and Sandboxes: Utilize Google BigQuery Sandbox, AWS Free Tier, and SQL sandboxes like DB Fiddle. iv) Open-Source Software: Experiment with Apache NiFi, Talend Open Studio, and Apache Airflow for ETL. (or most of the cloud platforms provide 1 month free subscription) v) Community Forums: Engage with communities on Stack Overflow, Reddit, and specialized forums like Data Warehouse Automation Forum.

Technology driven innovation is what drives evolution in any industry and subject area. Data warehousing is no exception. Now a days, innovative trends are better adopted, not alone by multi billion/million dollar technology, business companies but start ups in fast growing ecomnomies like India. Mergers and acquisitions of these start ups by leading tech companies is one crisp way to keep a watch if one wish to keep pace with evolution in Data warehousing. Always the best is to follow & subscribe to leading tech, industry analysts in this subject area. There are several other forums as well if one wishes to invest dedicated time and money into them.

Keep your foundations solid, many of the new concepts start from having well-structured foundations. If you try to grow in knowledge, do so in an orderly manner, following the best practices and always starting from taking care of the quality and certification of the data. Always refer to what you are doing so that you do not reinvent the wheel, but rather learn to accelerate and handle better in curves. Seek to know well a cloud computing tool such as AWS, GPC, AZURE, etc. If you master one tool the rest becomes easier.

Keeping up with data warehousing trends is important because it helps you use the latest technologies, improve performance, cut costs, integrate different types of data, enhance analytics, stay compliant and secure, and stay ahead of competitors.

To stay ahead in data warehousing, I'd continually update my skills in cloud-based data warehousing solutions like AWS Redshift, Google BigQuery, and Azure Synapse. Regularly engaging with industry forums, attending webinars, and obtaining relevant certifications will ensure I'm well-versed in the latest advancements. Additionally, staying connected with the data engineering community, exploring emerging technologies, and participating in hands-on projects will contribute to my expertise, allowing me to implement cutting-edge solutions and best practices in data warehousing.

In the fast-evolving field of data warehousing, staying ahead means continuous learning, hands-on projects, and active community engagement. I regularly dive into online courses, apply new technologies in real-world scenarios, and connect with industry peers through forums and LinkedIn groups. Keeping up with industry trends through research and pursuing relevant certifications are also key. My approach is about blending education, practical experience, and networking to not just keep pace but shape the future of data warehousing. Always open to connect and share insights!

One thing I've found helpful with getting mentors unintentionally is how I show other experts how curious I am about the field. Sometimes, asking someone to be your mentor can make that person uncomfortable. Instead, you can connect with the person, inform the person that you'll be asking him/her questions from time to time. Then don't stop there, show that you're inquisitive by asking relevant questions regularly. You'll notice that this person will warm up to you. As time advances, that person unknowingly becomes your mentor. This has happened to me several times that I can't even keep track of how many mentors I have because I was always inquisitive towards people I looked up to.

Consider becoming a mentor to junior professionals or individuals aspiring to enter the data warehousing field. Engage in ongoing dialogues with mentors, seeking advice on professional development, career paths, and industry trends.

When seeking feedback and mentorship from experienced colleagues in a technology you're learning, prepare specific questions to demonstrate your interest and eagerness to learn. During your meeting, actively listen to their insights, ask clarifying questions, and seek constructive feedback on your progress. If the conversation goes well, consider asking if they'd be willing to mentor you. Express gratitude for their time, keep them updated on your progress, and offer value in return, whether through sharing your expertise, assisting with projects, or being a supportive colleague.

Engage with other professionals in the data warehousing community through forums, meetups, and online communities. Collaborating with peers can help you gain new insights, exchange ideas, and stay informed about the latest developments in the field.

I've always found that mentoring interns is always a great way to give possible incoming professionals a sound crash course on corporate environments. Also, many interns bring the latest in technological applications being developed on college and university campuses across the country. Most interns in a Supply Chain program, will have a very high knowledge of what the latest and greatest applications are in the areas of Inventory and Finance.

Subscribe to training portals or feeds in this domain, visit some conferences, get more hands-on experience, read magazines and books, get certified, apply what you have learned, try to improve it and develop further. I found that ACM org, O'Reilly, Packt publishing, Medium and Feedspot could provide valuable resources. It is not complete list, just few of them... never stop learning, searching for new ideas and practicing - all is up to you!

Remember to be patient and have a continuous learning schedule to stay ahead of curve. The DWH industry is continuously evolving, so stay updated on the latest trends and advancements in data warehousing and ETL tools. Follow industry blogs, attend webinars, and participate in relevant discussions. Join online forums, communities, and LinkedIn groups related to data warehousing and ETL. Networking can provide valuable insights, tips, and potential job opportunities.

To stay ahead of the curve in data warehousing, continuously educate yourself on new technologies and trends, engage with the community through forums and conferences, and practice hands-on with modern data warehousing tools and platforms. Additionally, keep an eye on advancements in related fields like business intelligence, data science, and machine learning.

Deal with the topic of unit testing in the DWH environment / ETL testing in order to be able to identify and fix bugs as early as possible.

No ramo de TI é sempre fundamental come?ar com os fundamentos/base. A base é o suporte para tudo o resto que vem a seguir. Saber o porquê de cada coisa (n?o superficialmente, mas a essência ao mais baixo nível). Procure uma referência, um canal no youtube, acompanhe uma página de alguém que fala sobre o assunto, isso ajuda a estar mais por dentro do assunto e dá um melhor direcionamento.