Recent world events have exposed a wide range of issues in terms of how companies implement processes and use data to make decisions. It's abundantly clear that many enterprises came into the new year simply unprepared to make the sorts of decisions needed to persevere through difficult times, especially when the situation involves highly unexpected events.If you've found yourself trying to figure out answers to questions you've never even pondered, you may be wondering what tools could help you get ahead of these circumstances. There's a strong argument to be made about having a data warehouse in place that can make a major difference as organizations struggle to make these sorts of novel decisions. Whether you already have a big data warehousing system in place or are now just realizing the importance of one, it's also wise to think about precisely how prepared or unprepared you might be. Let's look at how a well-implemented data warehouse operation can help you get answers quickly in a rapidly evolving situation.What is a Data Warehouse? The difference between a massive collection of data and a data warehouse is that warehousing is designed to enable long-term use of data. A warehouse aggregates massive amounts of structured data from many sources, and it's designed to enable analysis and reporting. While a database can answer queries, the information in a data warehouse can be used to find relationships between different data points.
How a Solid Data Warehouse Can Help Decision-Making
Suppose you were a producer of paper products based in California at the beginning of 2020. By the end of January, sources of wood pulp from China have dried up and competition for American sources has become fierce. You want to start looking for suppliers in Latin America, but you don't know where to begin.A good database will have that information, but it won't have what a good data warehouse requires. For a data warehouse to contribute to a situation like this one, it needs to be able to tie together data about specific pricing and shipping costs for getting it to California. You don't want to have to research all of this due to the time and money you will be sacrificing in the process. Instead, a well-prepared data warehouse should be constantly digesting the necessary data to give you actionable information at the touch of your company's analytics dashboard. In fact, a top-quality system with predictive and prescriptive analytics should help you compare and contrast the available options in an instant. You might never have talked with many suppliers in new territories before, but your data warehouse is going to give you a diverse range of commodity pricing and shipping rates from the region so you can start having that conversation today rather than next week.
Structured Data and Being Prepared
You'll note that the example depends heavily on having large amounts of structured data available right away. A big part of being prepared for unforeseen events is investing early in the necessary infrastructure and data sources. You're going to want to make serious investments in:
It also means having highly failure-tolerant code constantly churning the inputs to ensure analysis can be run at a moment's notice. Likewise, actionable data is likely to require security, as it has the potential to become a trade secret you'll want to defend. Finally, you'll need people who can understand the intricacies of data science and decision-makers who've been fully onboarded with using analytics insights on a daily basis.
Conclusion
Becoming a highly prepared, data-centric business is a bit like quitting smoking: there is no better time than today. Regardless of where you're at in the process, it's a good idea to think about how prepared your operation is on the data side to help you respond to unexpected crises. Even if you feel thoroughly prepared at this very moment, a culture of constant improvement and preparedness will have your data warehouse ready to answer the next big round of questions you've never asked before.
