The course is part of this learning path
This course explores data sources and formatting, and how to present data in a way that provides meaningful information. You'll look at data access patterns, and how different interfaces allow you to access the underlying information. This course also provides a practical, real-world example of how all this theory plays out in a business scenario. By the end of this course, you will have a good foundational understanding of how to wrangle and visualize data.
If you have any feedback relating to this course, feel free to reach out to us at firstname.lastname@example.org.
- Understand the difference between data and information
- Learn how to make data useful in order to gain insights from it
- Learn how to store data correctly
- Understand how these techniques can be applied in the business world
This course is ideal for anyone who is required to interpret or understand data for reporting purposes or for use in machine learning initiatives.
To get the most out of this course, you should be familiar with relational databases such as SQL or NoSQL and some common data formats such as CSV and JSON.
So to wrap things up, data is turned into information through processing. This processing can take the form of formatting it to improve human readability, aggregation, and enrichment to combine it with other sources of truth, organizing it so that it's more readable and assessable, and providing analysis to detect hidden trends. Furthermore, visualization is key to making the information understandable. Insights and actual value is often driven through processing the data and combining it with a well-made visualization.
So hopefully this has given you a better understanding of how to prepare data, so as readable, usable, and useful when visualizing it. As always leave a comment or feedback if you have any thoughts, and I look forward to seeing you for the rest of the data engineering learning path. Thank you.
Course Introduction - Data vs. Information - How Do We Make Data Useful? - Storing Your Data - Case Study: Online Store
Calculated Systems was founded by experts in Hadoop, Google Cloud and AWS. Calculated Systems enables code-free capture, mapping and transformation of data in the cloud based on Apache NiFi, an open source project originally developed within the NSA. Calculated Systems accelerates time to market for new innovations while maintaining data integrity. With cloud automation tools, deep industry expertise, and experience productionalizing workloads development cycles are cut down to a fraction of their normal time. The ability to quickly develop large scale data ingestion and processing decreases the risk companies face in long development cycles. Calculated Systems is one of the industry leaders in Big Data transformation and education of these complex technologies.