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TECHINAUT

B LEVEL

4.5 (15)
NIELIT

DATA WAREHOUSEING AND DATA MINING

BE6-R4- B level (NIELIT)

Data warehousing and data mining are the essential components of decision support systems for the modern day industry and business. These techniques enable the knowledge worker (analysis, manager, executive) to make better and faster decisions. The objective of this course is to introduce the student to various Data Warehousing and Data Mining concepts and Techniques.

DATA WAREHOUSEING AND DATA MINING

9 Lessons

DATA WAREHOUSEING AND DATA MINING

120 Hours - (Theory: 48 hrs + Practical: 72 hrs)

DATA WAREHOUSEING AND DATA MINING

100+ students enrolled

Overview
Course Description

DATA WAREHOUSING AND MINING are two crucial components of big data. These two courses go hand in hand. These courses will help you make decisions based on big data. They also teach you the techniques and systems needed to process large amounts of data.Using machine learning and data mining techniques to analyze large datasets is the goal of this course. The course will examine methods in both fields and survey various applications.

What you'll learn
  • You can learn to organize and catalog data for easy searching and logical queries.
  • The course work data insights are critical to decision-making, so storing and processing large amounts of raw data will be crucial to the success of any organization.
  • The course will also give you the hands-on skills necessary to design and implement data warehouses effectively.
  • How to use data to make decisions.
  • This includes understanding business requirements, developing data warehouse models, and implementing multiple business intelligence solutions.
  • The course also introduces you to the field's most up-to-date concepts and technologies.
Course Content

  • DATA WAREHOUSEING AND DATA MININGLecture 1.1 An introduction to multidisciplinary filed of data mining

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 1.2 Different kind of Data on which Data Mining Applied

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 1.3 Classification of Data Mining System

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 1.4 Stress on Important of its Application Potential

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 2.1 Concepts of Data warehouse

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 2.2 Multidimensional Data Model: Data cube, Stars – Snowflakes

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 2.3 Life cycle of data Warehouse Implementation

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 2.4 Relationship between Data Warehouse and Data Mining

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 3.1 Data Preprocessing including Data cleaning

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 3.2 Discretization and concept Hierarchy generation

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 3.3 Description of Data mining query language with few example Queries

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 4.1 Introduction to Concept Description

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 4.2 Summarization Based Characterization

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 5.1 Association rule mining

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 5.2 Mining multilevel association rule

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 5.3 Association rule to correlation analysis

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 6.1 Issues regarding classification and predication

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 6.2 Classification methods including Decision tree induction

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 6.3 Prediction: Linear and Multiple Regression

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 7.1 Types of data in cluster analysis

    DATA WAREHOUSEING AND DATA MINING 02:53

  • DATA WAREHOUSEING AND DATA MININGLecture 7.2 Hierarchical Clustering, Density based Clustering

    DATA WAREHOUSEING AND DATA MINING 02:53

  • Mining Complex Types of Data Lecture 8.1 Data Mining issues In object oriented Databases

    Mining Complex Types of Data 02:53

  • Mining Complex Types of Data Lecture 8.2 Web mining: Web usage Mining

    Mining Complex Types of Data 02:53

  • Application of Data WarehousingLecture 9.1 Exploration of web sites on data warehousing

    Application of Data Warehousing 02:53

  • Application of Data WarehousingLecture 9.2 Corporate Houses and Research labs

    Application of Data Warehousing 02:53
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4.5 Instructor Rating

“ This is the second Photoshop course I have completed with Cristian. Worth every penny and recommend it highly. To get the most out of this course, its best to to take the Beginner to Advanced course first. The sound and video quality is of a good standard. Thank you Cristian. “

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Includes

  • course details 120 hours on-demand video
  • course details 69 downloadable resources
  • course details Full lifetime access
  • course details Access on mobile and TV
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Includes

  • course details Enrolled: 100+ students
  • course details Duration: 120 hours
  • course details Chapters: 9
  • course details Video: 120 hours
  • course details Level: Beginner