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Data Warehouse – Advantages and Threats

Normally when an SMB hears a phrase like ‘Data Warehouse’ the first thing that comes to mind is prohibitive costs. Also, there are horror stories about the implementation process due to the rigidity of the data modeling, which is measured in months, not days. What makes a data warehouse the preferred choice for enterprises is…

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.…