What if analysis data warehouse

To reach their goals, decision-makers need reliable predictive systems to evaluate beforehand the impact of strategic and tactical moves.

The design of the analysis Designing a what-if analysis requires a methodological framework able to detect the true levers to pull in the hands of analysts or even end-users. According to the literature, the following list may be considered as the theoretical skeleton for approaching a what-if analysis effectively: Goal analysis, aimed at determining which business phenomena are to be simulated, and how they will be characterized.

What-if analysis is not a one-way process, but it has to be iterated seeking for the best possible fit. The higher this fit, the more effectively analysts can actively manage the simulations. A data-driven approach to the strategy execution In this environment, the most successful businesses over the next decade will be those able to execute strategy better than their competitors by exploiting data to ensure the right alignment with strategy formulation. Limitations and new fields of research Although an input-by-input sensitivity analysis will increase the knowledge about which inputs drive the valuation, its use is limited.

Related Articles. However, organizations are finding it arduous to properly emerge ahead of the curve on this front. Digital transformation or cultural transformation? If we say that Data and Analytics strategies are increasingly present in all aspects of companies, communities, and even our personal lives, no one would be surprised. We all know this by now, but the million-dollar questions are: How do we do it? Where do we start? Is our company ready? We are fully immersed in the digital era that will lead us towards a cultural transformation.

The current circumstance takes us out of our comfort zone and we have a lot to gain and nothing to lose. Conference paper. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, log in to check access. Banerjee, J. Bellahsene, Z. Knowledge and Information Systems 4 2 Google Scholar.

Bernstein, P. In: Laender, A. ER LNCS, vol. Gupta, A. Information Systems 26 Google Scholar. Golfarelli, M. In: ECDM , pp. Mohania, M. Nica, A. In: Schek, H. They essentially sit atop the data warehouses as a layer that helps you query, analyze, and visualize your data. While data warehouses store data, business intelligence platforms analyze data. First, business intelligence tools integrate with many different sources , including your data warehouse.

They then provide an easy way to query the data in order to analyze data for trends and insights. Then, they make it easy to visualize and share data using dashboards and reports. These three steps, built on top of a good data warehouse foundation, will make it easier to follow through on the core promise of business intelligence: providing everyone in your organization with the ability to understand and act on data.

Once your data warehouse is in place, go ahead and connect it to your business intelligence platform. Chartio makes it as simple as possible with two ways to connect: direct connection or SSH tunnel connection.

Once connected, you can easily query and analyze your data from your data warehouse, gaining an enterprise-level view of your data pipeline. Sign up for a free Chartio account and you can have your data warehouse connected in a matter of minutes. When considering the right business intelligence BI platform for your business, you need to consider a full spectrum of features and characteristics, not to mention as many platforms as you can find.

Reporting with business intelligence BI used to require extensive data modeling and deep SQL knowledge in order to find insights. Modern BI reporting is thankfully much simpler. Download our free cloud data management ebook and learn how to manage your data stack and set up processes to get the most our of your data in your organization.

Data Tutorials. Business intelligence, as we know it today, would not be possible without the data warehouse. Where does all of this information go? Well, most of it goes in the data warehouses. What Is a Data Warehouse? Granular: The data they house is highly detailed and can be used in many different ways. Historical: They can host a continuous record of data over years and years. How Do Data Warehouses Work? How to Connect Your Data Warehouse to Your Business Intelligence Platform Once your data warehouse is in place, go ahead and connect it to your business intelligence platform.

Create an SSH Key. Install AutoSSH on your server. Add Chartio as a read-only user.