KPI Partners Blog
Exploring the different ways Tableau connects to data and whether dimensional modeling is necessary when using Tableau’s architecture.
Tableau has two primary ways to connect to data sources and work with them as shown in this simplified architecture diagram shown below .
Making a business intelligence (BI) project successful is a daunting task in itself not just because of the complexity and tools involved, but because it requires cooperation from different functional groups, multiple source systems, and gaining user acceptance from groups of users that are often resistant to change.
The challenges add on further when the BI projects are planned to be executed in an onshore-offshore model. There are obviously many positives and benefits from this approach which can make this model a highly successful provided we follow some of the best practices.
One of the challenges facing our clients is a disjointed landscape for their customer-facing business intelligence tools. This doesn’t happen in finance as everyone knows where the end product goes (CFO), nor does it happen much in product development. When it comes to customer analytics, many companies struggle with disjointed systems and difficulty getting the data they want. The sentence of, “I think we have that data….somewhere,” is often uttered at companies that have these issues.
by Parul Singh
The need for robust reporting and a structured enterprise data warehouse for educational institutions is becoming a necessity. This type of modern architecture empowers academic institutions with best-in-class reporting and analytic capabilities to increase faculty, staff and student productivity; streamline operations and institutional advancement; and ensure student success.
There are a few key star schemas that can aid universities and their stakeholders to make informed decisions and deliver a better student experience:
Endeca Information Discovery (EID) is a data discovery tool that helps business analysts to rapidly explore relevant data. If you are already using Oracle Business Intelligence Enterprise Edition (OBIEE) and wish to reuse the BI data models from Endeca Information Discovery, here are the options. The primary difference between both tools is that one is used for pre-defined analytics while the other is used for having a conversation with your data (analytics vs information discovery). The overall goal for both approaches is to get the most value out of the data available.
A quick Google search for “Tableau Data Security” returns a link to a Tableau knowledge base article for User Filters and Row Level Security. The knowledge base article clearly lays out the options available for implementing data security – defined as the ability to control what data a user sees. The goal here is to not regurgitate that content, but to examine each of the two data security options laid out by Tableau and determine how they fit various use cases in the enterprise context.