Introduction to Data Analytics

Duration: 3 days
Language: English
17 NASBA CPE Credits (live, in-class training only)
Level: Foundation

As data evolves for organizations, employees must understand the value of the data they hold. This Data Analytics Introduction provides a clear understanding of data analytics's purpose, tools, and techniques. In addition, it will help attendees to plan the data and digital strategy for their organizations.

Data Analytics Introduction Delivery Methods

In-Person
Online
Upskill your whole team by bringing Private Team Training to your facility.

Data Analytics Introduction Training Information

Back at work, attendees will be able to:

Define what Data Analytics is and how it helps with business-focused decision-making
Understand the fundamentals of pattern recognition
Differentiate between data roles such as Data Analyst, Data Scientist, Data Engineer, Business Analyst, and Business Intelligence Analyst.
Recognize the value, terminology, and challenges of Business Intelligence
Understand how Data Mining builds knowledge, insights, patterns, & data advantages
Appreciate the usefulness of data visualization, visual patterns, and Infographics for stakeholder communication
Improve awareness of the value of the data your organization holds and how to manipulate it
Have excellent fundamental knowledge of data, how it is captured, and how it is visualized for us in the business
Position Data Warehouses as data management facilities that help to:
- Create reports and analysis
- Support managerial decision making
- Engineered for efficient reporting and querying

Training Prerequisites

A basic understanding of what data is and the function of data analysis

Certification Information

Learning Tree Exam included

Data Analytics Introduction Training Outline

Chapter 1: Data Analytics Introduction

Business Intelligence

Example: MoneyBall: Data Mining in Sports

Pattern Recognition

Types of Patterns
Finding a Pattern
Uses of Patterns

The Data Processing Chain

Data Database
Data Warehouse
Data Mining
Data Visualization

Data Analytics Terminology and Careers

Review Wheel

Chapter 2: BI Concepts & Applications

Introduction

Example: Schools and Academies
BI in Education

BI for Better Decisions

Decision types

BI Tools
BI Skills

BI Applications

Customer Relationship Management
Healthcare and Wellness
Education
Retail Banking
Financial Services
Insurance Manufacturing
Supply Chain Management
Telecom
Public Sector

Conclusion

Review Wheel

Case Study Exercise

Chapter 3: Data Warehousing

Introduction

Example: University Health System – BI in Healthcare

Design Considerations for DW

DW Development Approaches

DW Architecture
Data Sources
Data Loading Processes

Data Warehouse Design

DW Access
DW Best Practices
Data Lakes

Conclusion

Review Wheel

Case Study Exercise: Step 2

Chapter 4: Data Mining Introduction

Introduction

Example: Target Corp – Data Mining in Retail

Gathering and selecting data

Data cleansing and preparation
Outputs of Data Mining
Evaluating Data Mining Results

Data Mining Techniques

Tools and Platforms for Data Mining
Data Mining Best Practices
Myths about data mining
Data Mining Mistakes

Conclusion

Review Wheel

Case Study Exercise: Step 3

Chapter 5: Data Visualization

Introduction

Example: Dr. Hans Rosling - Visualizing Global Public Health

Excellence in Visualization

Types of Charts
Visualization Example

Tips for Data Visualization

Conclusion

Review Wheel

Case Study Exercise: Step 4

Chapter 6 Popular Data Mining Techniques

Decision Trees

Introduction
Example: Predicting Heart Attacks using Decision Trees
Decision Tree problem
Decision Tree Construction

Regression and Time Series Analysis

Correlations and Relationships
A visual look at relationships
Regression
Non-linear regression
Logistic Regression
Advantages and Disadvantages of Regression
Time Series Analysis

Artificial Neural Networks

Introduction
Example: IBM Watson - Analytics in Medicine
Principles of an Artificial Neural Network
Business Applications of ANN Design
Representation of a Neural Network
Architecting a Neural Network
Developing an ANN
Advantages and Disadvantages of using ANNs
Conclusion

Select Commercial or Government Pricing

$2,785

3-day instructor-led training course
Hands-on labs included
Learning Tree Exam included
After-course coaching available

Would you like to take this course as a team?

Mar 25 - 27 9:00 AM - 4:30 PM EDT

Ottawa or Virtual
May 13 - 15 9:00 AM - 4:30 PM EDT

Herndon, VA or Virtual
May 27 - 29 9:00 AM - 4:30 PM EDT

New York or Virtual
Jun 16 - 18 9:00 AM - 4:30 PM EDT

Ottawa or Virtual
Jul 8 - 10 10:00 AM - 5:30 PM EDT

Austin or Virtual
Aug 12 - 14 9:00 AM - 4:30 PM EDT

Herndon, VA or Virtual
Sep 9 - 11 9:00 AM - 4:30 PM EDT

Ottawa or Virtual
Oct 14 - 16 9:00 AM - 4:30 PM EDT

New York or Virtual
Nov 23 - 25 10:00 AM - 5:30 PM EST

Austin or Virtual

Scroll to view additional course dates

$2,785

3-day instructor-led training course
Hands-on labs included
Learning Tree Exam included
After-course coaching available

Would you like to take this course as a team?

Mar 25 - 27 9:00 AM - 4:30 PM EDT

Ottawa or Virtual
May 13 - 15 9:00 AM - 4:30 PM EDT

Herndon, VA or Virtual
May 27 - 29 9:00 AM - 4:30 PM EDT

New York or Virtual
Jun 16 - 18 9:00 AM - 4:30 PM EDT

Ottawa or Virtual
Jul 8 - 10 10:00 AM - 5:30 PM EDT

Austin or Virtual
Aug 12 - 14 9:00 AM - 4:30 PM EDT

Herndon, VA or Virtual
Sep 9 - 11 9:00 AM - 4:30 PM EDT

Ottawa or Virtual
Oct 14 - 16 9:00 AM - 4:30 PM EDT

New York or Virtual
Nov 23 - 25 10:00 AM - 5:30 PM EST

Austin or Virtual

Scroll to view additional course dates

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Data Analytics Introduction FAQs

40% of the course time is spent in hands-on exercises

Yes, this course is a perfect starting point for someone entering Data Analytics

No, this course is technology neutral

This course applies to anyone looking for an introduction to data analytics, including data warehousing, data mining, and data visualization.
Senior Managers, Business Analysts, Data Analysts, Data Scientists, Database Administrators
They come from all types of industries, with data being the common element, i.e., Any industry that needs help leveraging the advantages of data analytics and the data analytics industry itself.
Senior Managers, Business Analysts, Data Analysts, Data Scientists, and Database Administrators.
- Senior managers will find it helpful to understand data analytics's advantages for the business.
- Business analysts will find this course helpful in understanding the eventual output of requirements and modeling.
- Students wishing to pursue a course in Data Science or Data Analysis will find this course useful as it gives an overview of the Data Analytics field.

Introduction to Data Analytics

Data Analytics Introduction Delivery Methods

Data Analytics Introduction Training Information

Data Analytics Introduction Training Outline

Chapter 1: Data Analytics Introduction

Chapter 2: BI Concepts & Applications

Chapter 3: Data Warehousing

Chapter 4: Data Mining Introduction

Chapter 5: Data Visualization

Chapter 6 Popular Data Mining Techniques

Live Instructor $2,785

Live Instructor $2,785

Data Analytics Introduction FAQs

How much time is spent on hands-on exercises?

I am just starting out in Data Analytics; do you recommend I start with this course?

Does it matter what technology my organization is using?

Who should attend this Data Analytics course?

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