Here's how you can make informed decisions as a data warehousing professional.

Understand Your Data: Know the data you’re working with. Understand its source, its format. Stay Updated with Latest Technologies: Data warehousing technologies are constantly evolving. Stay updated with the latest tools and technologies like Snowflake, Redshift, BigQuery etc. Master SQL: SQL is the language of data. Being proficient in SQL can help you manipulate and analyze data effectively. Data Modeling: Understand different data modeling techniques such as Star Schema, Snowflake Schema etc. Choose the one that fits your requirements the best. Performance Tuning: Learn how to optimize your queries and your data warehouse design for better performance. Security: Understand the importance of data security and compliance.

As Dylan Accorti already mentions, it is key to understand your organization in order to be able to understand your data. It also links to what I'm missing in the bulletpoints; Know how business processes interact, for it is key to the effectiveness of information. Subtle or overlooked interactions can be mined when enough data is integrated but you will lose business support before that if you can not present information in a way that not only problems can be visualized but also solutions. Just setting clear goals and analyzing trends is not enough, or at least a missed opportunity to really add value over single topic reports.

As correctly mentioned, today there are a number of tools to help in warehousing the data for an organisation efficiently. Implementation of a data warehouse revolves around multiple areas and it is paramount that one chooses the best tools for each of these individual areas as per the technological landscape specific to the organisation. The choice of these tools also revolve around the overall technological vision of an organisation. For example the data handling policies of an organisation, the nature of the source systems, the speed of incoming data, the mode of distribution of generated insights to the end users, etc. These play a vital role in deciding the tools and technologies for a data warehouse.

In the realm of data warehousing, it's not uncommon for systems to become stale over time. This article hits the mark with its insights, but there's a critical point to remember: what starts out perfectly aligned can drift if not regularly adjusted. Knowing your data, setting clear goals, and using the right tools are foundational. Yet, as user behavior evolves, your data warehouse must adapt. Regularly analyzing trends and getting user feedback from your observations ensures your decisions stay relevant and impactful. Collaboration and staying informed are vital, but continuous adjustment is key. Data warehousing isn't a set-it-and-forget-it task; it's an evolving process. Keep refining to maintain accuracy and drive strategic success.

Analysing trend is an important prospective of data-ware housing.As that is way it can be helpful for business in decision making.If we analyse the data and find a trend out it.It will help us in predictive analysis as well as taking preventive steps in case we don't want to repeat some situation.

I cant agree more with this article as analysing trends over time from historical data is actually one of the key use cases of data warehousing to help businesses take informed decisions. For this reason data warehousing is not just the process of storing chunks of historical data in a storage but also storing it in the most optimally modular fashion, so that it can help in getting insights about the performance of a business quickly as seen from different dimensions.

The landscape of data warehousing has witnessed tremendous technological developments and enhancements. From the days when data warehouses were built on top of monolithic databases to the current era where distributed computing and massive parallel processing have become the key to any successful implementation of a data warehouse, things have been changing substantially for the better. Today there is no limitation on the nature, volume or even the speed of the data to be handled by a data warehouse. Its of utmost importance that one stays upto speed with these rapid developments because in my experience the fundamental concepts and best practices of data modelling may also change with changes in the underlying implementations of DWs.

Be wary of the hype! The hallmark of a successful data warehouse professional lies in prioritizing solutions with a demonstrably positive impact on the organization's data management challenges. Focusing on long-term sustainability and maintainability ensures that chosen technologies can evolve alongside business needs. Ultimately, success hinges on measuring the impact of the data warehouse on tangible business goals, not simply on its adherence to the latest trends.