Data Mining Data Modelling Data Warehouse Predictive Analytics 
Smart Data Collective
NOVEMBER 18, 2020
You may not even know exactly which path you should pursue, since some seemingly similar fields in the data technology sector have surprising differences. We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. What is Data Science?
Astera
JANUARY 23, 2024
Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.
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Data Pine
MARCH 31, 2022
This could involve anything from learning SQL to buying some textbooks on data warehouses. A data scientist has a similar role as the BI analyst, however, they do different things. While analysts focus on historical data to understand current business performance, scientists focus more on data modeling and prescriptive analysis.
The BAWorld
NOVEMBER 22, 2021
Data Modeling. Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Conceptual Data Model. Logical Data Model : It is an abstraction of CDM. Data Profiling.
Insight Software
MAY 1, 2023
All of the above points to embedded analytics being not just the trendy route but the essential one. Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” Diagnostic Analytics: No longer just describing.
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