Data Integration,
Management, Warehousing, & Teradata

ABOUT THE PROGRAM

Talend data integration provides an easy way to get integration projects done quickly and with less overhead. It has several tools that make it a powerful, cost-effective suite.

Data management/predictive analytics uses techniques, such as statistics and machine learning, to build predictive models, often using big data to test and validate these models. It is becoming a key component for organizational success.

Data warehousing is the secure electronic storage of information by a business or other organization. The warehouse becomes a library of historical data that can be retrieved and analyzed in order to inform decision-making in the business.

Teradata provides a relation database system for data storage that offers various tools and utilities for management, administration, and querying. It offers a high quality system including a parallel database architecture providing a “share nothing” architecture.

Occupational Objectives: Data Integration Analyst, Data Miner, Data Warehousing Business Analyst, Data Warehousing Developer

Prerequisites: HS Diploma/GED, basic PC skills and familiarity with the Internet

Tuition: $997

Duration: 57 Hours

Students will have access to the program for 1 full year.

This program includes e-books.

To learn more about ETI’s tuition and financial aid options, click here.

COURSE Outline

Talend Data Integration

  • Getting Started with the Software and Integrating Data

  • Working with Data Mapping, Jobs, and Automation

Predictive Analytics

  • Predictive Analytics and Big Data

  • Process and Application

  • Key Statistical Concepts

  • Correlation and Regression

  • Data Collection & Exploration

  • Data Mining, Data Distribution, & Hypothesis Testing

  • Data Preprocessing

  • Data Reduction & Exploratory Data Analysis (EDA)

  • K-Nearest Neighbor (k-NN) & Artificial Neural Networks

  • A/B Testing, Bayesian Networks, and Support Vector Machine

  • Clustering Techniques

  • Linear and Logistic Regression

  • Text Mining & Social Network Analysis

  • Time Series Modeling

  • Machine Learning, Propensity Score, & Segmentation Modeling

  • Random Forests and Uplift Models

  • Model Life Cycle Management

  • Model Development, Validation, & Evaluation

Data Warehousing

  • Data Warehousing Essentials

  • Data Warehousing with Azure

  • Data Warehousing with Hadoop

Teradata

  • Teradata Basics: Relational Database and Data Warehouse Basics

  • Teradata Basics: Communication and Database Security

  • Teradata Basics: Data Storage and Access Methods

  • Teradata SQL: The SELECT Statement, Joins, and Subqueries

  • Teradata SQL: Functions, Data Conversions, and Working with Time

  • Teradata SQL: DDL, DML, and SQL Optimization