Cracking the Data Code – Data Flows

Categories: Business, Data work
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About Course

Master the Basics of Data work

This “Data Flows” module provides a condensed introduction to optimizing your data streams. In this 2.5-hour video lesson, you’ll learn how to identify key pain points, streamline your data flows, and start seeing improvements in your organization’s efficiency and productivity. This module is perfect for those who want to dip their toes into the world of data flows and their business value-adds, or need a quick refresher before diving deeper into the full course.

This course is designed as an intro to the subject and targets people involved in the creation and management of data projects. For a more in-depth view of data work, please check out its sequel course (available here on CourseVolt).

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What Will You Learn?

  • In this course, you will learn:
  • - what data flows are
  • - how they are useful in an org, and
  • - some essential aspects of data work.

Course Content

1. Why Is Data Important?
1.1 Introduction 1.2 Data fosters better understanding of situation at hand 1.3 Data enables better assessment of problems in the org 1.4 Data brings about better decisions 1.5 Data enables better communication of important information in the org 1.6 Data helps make predictions of KPIs & other useful variables 1.7 Data enables the building of information & knowledge

  • 04:26
  • 06:04
  • Check what you’ve learned
  • 1.3 Data enables better assessment of problems in the org
    03:17
  • Check what you’ve learned
  • 1.4 Data brings about better decisions
    02:50
  • Check what you’ve learned
  • 1.5 Data enables better communication of important information in the org
    04:25
  • Check what you’ve learned
  • 1.6 Data helps make predictions of KPIs & other useful variables
    05:35
  • Check what you’ve learned
  • 1.7 Data enables the building of information & knowledge
    03:17
  • Check what you’ve learned

2. What is data work?
2.1 Introduction 2.2 Data Governance 2.3 Data Engineering 2.4 Data Analytics / Data Science 2.5 Data Visualization 2.6 A.I. related Work 2.7 Data-based Decision-making 2.8 Knowledge Bases 2.9 Privacy Matters

3. What Are Your Key Pain Points?
3.1 Introduction 3.2 Business needs 3.3 Aims & Objectives 3.4 Business strategy 3.5 Measuring and managing pain points 3.6 Solutions already in place

4. How and When Can Data Help?
4.1 Introduction 4.2 Through EDA 4.3 Through Predictive Analytics 4.4 Through Competition Analysis 4.5 Through A/B testing of potential solutions 4.6 Through weighing of factors in a decision 4.7 Through A.I. for better communication of relevant info and knowledge

5. How Can You Optimize Your Data Flows?
5.1 Introduction 5.2 Evaluate their costs and value-adds 5.3 Prioritize accordingly 5.4 Explore synthetic data options 5.5 Explore data trading 5.6 Explore web scraping 5.7 Store data properly & apply proper privacy protocols

Evaluation Test
Exercises to help you test your knowledge and make it your own.

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