Data warehousing and data mining tutorial

  • Basic elements of data warehouse

    A data warehouse is a central repository of information that can be analyzed to make more informed decisions.
    Data flows into a data warehouse from transactional systems, relational databases, and other sources, typically on a regular cadence..

  • Basic elements of data warehouse

    Data science bootcamps, for instance, are a great way to learn data mining essentials in a more practical, hands-on manner.
    In addition, some aspiring data professionals learn industry basics while working on the job or through self-taught options..

  • What is data warehouse tutorial point?

    A Data Warehouse is used for reporting and analyzing of information and stores both historical and current data.
    The data in DW system is used for Analytical reporting, which is later used by Business Analysts, Sales Managers or Knowledge workers for decision-making..

A data warehouse is constructed by integrating data from multiple heterogeneous sources. It supports analytical reporting, structured and/or ad hoc queries  DWH - Data MartingConceptsPDF VersionDWH - Schemas

Characteristics of Data Warehousing

1. Integrated 2. Time variant 3

Data Mining

Data mining refers to extracting knowledge from large amounts of data. The data sources can include databases, data warehouse, web etc

What Kind of Data That Can Be mined?

1. Database Data 2. Data Warehouse 3

Scope of Data Mining

1. Automated Prediction of trends and behaviours: Data mining automates … 2

What are the steps in a data warehouse process?

Data Extraction: The first step in the data warehouse process is to extract data from various sources such as transactional systems, spreadsheets, and flat files

Data Cleaning: After the data is extracted, it is cleaned to remove any inconsistencies, errors, or duplicates


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