To drive progressive digital transformation with analytics, you need to have a solid understanding of data warehousing and business intelligence (BI) platforms. Even more importantly, you need to understand that they are more than just platforms: they are the portals to insight and strategic decision-making for your business. Governed data curation can bridge the gap between raw data for the sake of numbers and data storytelling as a new language to use when making decisions about how your business is reaching and impacting your audience. Tableau has found insights showing that data storytelling is the new language of corporations.
What is data warehousing?
A data warehouse collects and stores data from various sources. Housing or storing the data in a digital "warehouse" is similar to storing documents or photos on the cloud. Having a place to store your data makes it easier to use and provides more insights, but on a larger scale. You can import historical data or timely data feeds to report the most recent and integrated data. You can use a data warehouse for analytical purposes and business reporting. However, to make full use of all of your data, you should create an integrated data strategy and an authentic audience story. We recommend combining your data warehouse with your other business intelligence practices.
What is business intelligence?
Business intelligence is the collection, methodology, organization, and analysis of data. When most people use the term business intelligence or BI, they are referring to the platforms and practices for the collection, integration, analysis, and presentation of business information. But BI is more than that—it allows for better business decision-making by ensuring decisions are strategic. With BI, you have data to back up why one option might be more successful than another based on past performance and research.
Don’t pit business intelligence vs. data warehouses
Business intelligence and data warehousing are similar concepts that operate in the same space, yet are very different. Both BI and data warehouses involve the storage of data. However, business intelligence is also the collection, methodology, and analysis of data. Meanwhile, a data warehouse is fundamentally the storage and organization of that data to provide for BI processes. Maintaining and deploying a data warehouse is so critical to BI that they are often collectively referred to as BIDW.
How can data warehousing power a successful business intelligence strategy?
For starters, as discussed earlier, an efficient data warehouse can speed up the load time for preparing and analyzing data. It also can improve security, data compliance, storage capacity, integration compatibility, and shareability of data. Snowflake’s data warehouse solution is a good example of how to learn the importance of a good data warehouse you can utilize with your business intelligence practices.
Data warehousing and business intelligence combined have evolved to include more processes and activities.
Having the right data in your data warehouse and the right business intelligence leveraging that data allows for many practices that can drive strategic decision-making. Options include, but are not limited to:
Also known as knowledge discovery, data mining is a process used to extract usable data from a more extensive set of raw data. This process helps you discover trends, themes, or patterns in large amounts of big data.
Metrics are used to measure the behavior, activities, and, yes, the performance of a business, its employees, or specific campaigns. While performance metrics are the result of analysis, those results can then be collected for further analysis. Performance metrics measure required data within a range, allowing a hypothesis to be formed, proven, or disproven according to previously determined business goals.
Within business intelligence and data warehouses, analysts and business teams query data to check its validity or accuracy. Successful BI helps businesses and organizations ask and answer questions of their data and have the right data in place to get reliable, quantitative information in those answers.
Data analysis has several components; statistical analysis is one of them. In the context of business intelligence and data warehousing, statistical analysis involves collecting and reviewing data samples. In statistics, a sample is a selection drawn from a total population of data. It is critical to have the data warehoused and connected to your BI processes for the analysis to be as accurate, thus leading to smart, strategic decisions.
Data visualization means taking data and representing it visually to improve understanding and better inform decisions. These can be charts, diagrams, data stories, and infographics to show answers to questions and provide data validation for decisions. Presenting data as a spreadsheet can be a cumbersome and dry experience, but visualizing data often helps bring information to life in a more compelling and effective way.
Data storytelling is translating data analyses into layman's terms to influence or inform a strategic business decision. Having the right warehouse for your data and the most reliable business intelligence tools will make it easier to compile and the stories that much more pursuasive.
Should I use a data warehouse in combination with my business intelligence platform?
Short answer: If you can afford to do it effectively, yes. While some organizations practice business intelligence without the use of a data warehouse, there are downfalls to that approach, usually due to time or budget. Namely, that processing the needed data can put a strain on transactional databases, reduce performance, and increase load time. This slows the analysis-to-insight process. Also, by not combining your data sources, they prove less efficient and can lack accessible historical information. In other words, transactional databases cannot do the same job as a data warehouse. A strong relationship with your data is critical when it comes to making the right, timely decisions for your organization. Using a robust data warehouse partnered with business intelligence best practices makes this possible. Learn more about how we work with our partners to provide data warehousing and BI solutions.