Data Primer Training Course | DevelopIntelligence

Course Summary

The Data Primer training course is designed to establish a baseline knowledge of the strengths, weaknesses, opportunities and risks surrounding data-based solutions. In this course, students will get an overview on data handling practices and some of the introductory technologies that support data initiatives.

The course begins with students being introduced to common terminology and their definitions as well as the most common issues to be faced when leveraging big data oriented systems. Next, the course covers the essential data flows and common technologies to illustrate how this is accomplished. The course concludes with students presenting findings with reports and dynamic visualizations.

Purpose

Learn about the strengths, weaknesses, opportunities and risks surrounding data-based solutions.

Audience

Software engineers who want to gain valuable insight as well as hands-on skills across an extensive landscape of data tools, techniques, and capabilities.

Role

Data Engineer - Data Scientist

Skill Level

Introduction

Style

Workshops

Duration

2 Days

Related Technologies

Databases

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Productivity Objectives:

Analyze data challenges: prescriptive, predictive, diagnostic, descriptive.
Craft data processing and analysis frameworks.
Verify that data are clean and hygienic.
Cluster and scale solutions to adapt to large problem sets.
Present findings through reports and dynamic visualizations.

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about our training

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
Expert Practitioners

Industry experts with 15+ years of industry experience that bring their battle scars into the classroom.
Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
Fully Customized

One-size-fits-all doesn't apply to training teams. That's where we come in!

What You'll Learn

In the Data Primer training course, you'll learn:

The Current State of Big Data
- What is happening in Data Science
- Top Reasons for Adopting Big Data
- Big Data vs Data Science vs ML vs DL
- What does it mean to be data driven
The Data Pipeline
A Day in the Life of a Data Scientist
The Scientific Process
- How to write a good hypothesis
The Core of the Data Stack
Reference Technologies for New Data Consumers
- HDInsight
- Hive
- Sqoop
- Nifi
- Zeppelin
Data in the Cloud
- Leveraging the services in Azure
- HDInsight
Getting Data In
- Ways to get data in
- Use Sqoop as an example tech to bring MSql Data into HDInsight
Making Data Accessible
- The common language: SQL
- Use Hive to query data
Data Pipelines
- What are pipelines?
- Use Apache Nifi to create data flows
Data Visualization
- Importance of data visualization
- Making data understandable
- Using Zeppelin for visualizing data