The Significance Of Metadata In BI Projects
This blog post will explore the importance of metadata in designing a Business Intelligence (BI) project, and how BI4Dynamics leverages it to automate data warehousing Firstly, let’s define metadata. It refers to the additional information and descriptions of data. For instance, when taking a picture using an iPhone, the metadata information includes the geolocation and […]
Data Quality In BI Projects – How To Prevent BI Project Failing Using Data Validation
Why Data Quality matters and How BI4Dynamics Addresses it? The success or failure of a Business Intelligence (BI) project hinges on one crucial factor: Data Quality. To ensure accurate data is used, BI4Dynamics provides a Data Validation process during the Proof of Concept phase (PoC). Firstly, how BI4Dynamics performs Data Validation? From BI4Dynamics, you would […]
Indexing
Indexing Data Warehouse Tables Too many or too few indexes can hurt performance. Non-active indexes may disturb SQL server in generating the optimal execution plan. Managing indexes can become an art that only experienced professionals can make right. Not accidentally, models in BI4Dynamics data warehouse are know to the same engine that generates the indexes. […]
Microsoft Power BI Advantages And Threats
Microsoft Power BI has lent itself well to the SMB space because it supports a variety of data sources, it is relatively easy to create data models and it enables simple deployment with immediate results. Its usage, at least at the beginning of a project does not require specialist BI knowledge. If your main data source […]
Business Central (BC) Cloud BI4Dynamics Data Transformation
Introduction This post describes the data transformation process from Microsoft Dynamics D365 BC SaaS to visualization tools (Power BI, Excel). It includes also the total monthly cost for the project. Data transformation diagram Data transformation is done in the following steps Data transformation process BC database BI4Dynamics reads data from a BC replica; […]
