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Blockchain Technology for Data Analysis

Create blockchain applications for data analytics

Topic: Software Development
Shawn Gordon

You’ve heard it before. Blockchain is too complicated, and it’s only used in supply chain and cryptocurrency applications. But blockchain technology and decentralized databases also give data scientists and data analytic professionals the power to conduct high-quality predictive analysis, work with big data, and do large computational processing. Using decentralized consensus algorithms and cryptography, blockchain technology can provide data scientists with validated data to make their prediction and data analytics much easier.

Join expert Shawn Gordon to learn how to combine blockchain technology with data analytics—particularly for large decentralized applications (also known as DApps). You’ll get a quick refresher on blockchain technology and concepts before walking through building a DApp for storing and managing data in a distributed database system, as opposed to a traditional centralized one. Along the way, you’ll discover how to perform normal data analysis tasks on your DApp with Ethereum Swarm.

What you'll learn-and how you can apply it

By the end of this live online course, you’ll understand:

  • Blockchain technology basic concepts
  • How decentralized consensus algorithm and cryptography work
  • How to develop a DApp on Ethereum from scratch
  • How to leverage the power of distributed storage platform Ethereum Swarm in data analytics
  • How to perform data analytics and predictive analysis on blockchain DApps
  • Best practices for blockchain integration with data analytics

And you’ll be able to:

  • Use cryptography
  • Develop blockchain applications
  • Create DApps as a distributed database system
  • Perform data analytics and predictive analyses on a distributed database system
  • Compare the computational performance of blockchain-based and traditional data analytics

This training course is for you because...

  • You want to learn how to use blockchain technology to perform data analytics.
  • You work with big data and want to understand what opportunities blockchain offers for quality predictive analysis.
  • You want to build your own blockchain DApp on Ethereum.
  • You want to learn how to use Ethereum Swarm.

Prerequisites

  • A working knowledge of programming with Python and JavaScript
  • Familiarity with blockchain concepts

Recommended preparation:

Recommended follow-up:

About your instructor

  • Shawn Gordon is a software professional with over 20 years of design and development experience. Since 2016, Shawn has been heavily involved with blockchain projects such as Ethereum, Hyperledger Fabric, Hyperledger Sawtooth, and IOTA. Shawn has written for a variety of magazines, including Bitcoin Magazine, and has published over 400 articles. He’s also a senior blockchain instructor and developer at DC Web Makers.

Schedule

The timeframes are only estimates and may vary according to how the class is progressing

Introduction to blockchain and its development environments (15 minutes)

  • Presentation: Introduction to blockchain technology; blockchain transactions; blockchain 1 and 2 generations; consensus algorithms
  • Hands-on exercises: compare the database in a blockchain network with a traditional centralized database
  • Q&A

Cryptography and encryption technology (10 minutes)

  • Presentation: Cryptography; how data is encrypted in a blockchain application
  • Hands-on exercise: Encrypt two sets of data
  • Q&A

Introduction to Ethereum (30 minutes)

  • Presentation: What is Ethereum, building a Ethereum blockchain application in Ethereum Studio
  • Hands-on exercise: How to build a blockchain application in Ethereum
  • Q&A
  • Break (5 minutes)

Introduction to Ethereum Swarm (55 minutes)

  • Presentation: What is Ethereum Swarm; how a blockchain distributed storage platform works, how to build Ethereum applications on Remix, how a blockchain differs from a traditional database
  • Hands-on exercises: Determine how Swarm distributed storage differs from traditional storage engines like MongoDB or MySQL;
  • Q&A
  • Break (5 minutes)

Data analytics on Ethereum (35 minutes)

  • Presentation: Role of blockchain in data science; run analytics on Ethereum Smart Contracts; Ethereum dataset visualizations, analytics for Ethereum development
  • Hands-on exercise: How to improve Ethereum performance by utilizing data analytics
  • Q&A
  • Break (5 minutes)

Review of blockchain development (15 minutes)

  • Presentation: Ethereum and Solidity; Hyperledger Fabric; Corda; putting things together;
  • Wrap-up and Q&A (5 minutes)