Data Nuts & Bolts: Fundamentals of Data
Data
| Beginner
- 10 videos | 29m 53s
- Includes Assessment
- Earns a Badge
Dealing with large amounts of data is essential to any modern business and to become a data-driven organization, leaders and decision-makers must establish a deeply ingrained data culture. Use this course to understand the underlying principles of analyzing data and get familiar with terms related to data in order to properly deliver data-related projects. This course will help you identify the basic concepts and processes related to data analysis, modern data sources, and data pipelines. You'll also discover fundamental principles of data storage, migration, and integration, along with common methods for data visualization and reporting. Having completed the course, you'll be well versed in foundational concepts of data, related terminologies, and various data processing methods.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this courseDistinguish between raw data, information, applicable knowledge, and general wisdomDescribe common sources of modern data and major data formats in useDefine concepts essential to data science like dataset, database, data analytics, data aggregation, and time seriesOutline disaster recovery plans and list common data backup strategies and tools
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Describe how to perform data migration and explain the functionality of common tools like extract, transform, and load (etl)Identify best practices for data integration and its advantagesRecognize the importance of data visualization and reporting and tools commonly used for the sameDefine the functionality behind common data processing languages such as sql and list the main commands used in themSummarize the key concepts covered in this course
IN THIS COURSE
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1m 16sIn this video, you’ll learn more about your instructor and this course. In this course, you’ll learn some important and fundamental concepts, terminologies, and methods related to Data and Data Management. You’ll also learn some important procedures and practices related to data. These include Data migration, Data integration, Data transformation, Data backup, Data visualization, and some Data engineering Languages. FREE ACCESS
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2mIn this video, you’ll learn more about data, knowledge, information, and wisdom. Knowledge usually refers to know-how, or the ability to solve a problem or answer a query. Knowledge has a profound and fundamental relationship with data, information, and wisdom. Data refers to raw and unstructured facts, numbers, and figures which convey a message. Data in its raw form is not structured or organized in any way and provides no further details to its viewers. FREE ACCESS
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6m 39sIn this video, you’ll learn more about data generation and data formats. You’ll see all organizations rely on tools and methods for generating data. You’ll learn about several common data types, observational, experimental, compiled, and simulated. Observational data is a result of direct human observation and is usually collected in real-time. Experimental data is generated through clinical research and investigation. FREE ACCESS
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3m 41sIn this video, you’ll learn more about data. You’ll learn data can be classified into two groups, primary data and secondary data. Primary data is data that a person or a group collects by themselves, and secondary data is data collected by a third party. You’ll learn about 12 common data terminologies. Database refers to a repository for organized data. Databases store data in tables. Data analytics refers to processes that explore data. FREE ACCESS
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2m 34sIn this video, you’ll learn more about the concept of data storage, backup, and retention. You’ll learn the three main methods of backup. These are full backup, differential backup, and incremental backup. Data storage is the capture and retention of data that needs to be retained for historical, archival, or legal purposes. Computers have short-term and long-term memory. You’ll learn the three main backup methods and their descriptions. FREE ACCESS
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3m 57sIn this video, you’ll learn more about data migration. Data migration is one of the most complex and critical parts of every data transformation project. Careful planning is essential in reducing risk and maximizing a project's chances of success. Data migration is required in many scenarios and typically involves six main steps. You’ll go over all six steps here. The first step is planning. FREE ACCESS
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3m 27sIn this video, you’ll learn more about data integration. Data integration is an important concept involving combining data from various data sources into a unified location. All data integrations have a few things in common. Data integrations begin with data ingestion, and then step into cleansing the data prior to the actual integration. These integrations require performing correct ETL mapping to ensure consistency and compatibility. They also require identification of sources, targets, and servers. FREE ACCESS
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2m 25sIn this video, you’ll learn more about data visualization. You’ll learn this is any visual representation of data. Examples include graphs, charts, and diagrams where the relationship between the data and images is communicated. Data visualization allows the identification of trends and patterns. Data visualization helps people better understand large data sets by providing visual representations. Data visualization also makes it easy to conduct analysis and make predictions about the future. FREE ACCESS
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2m 54sIn this video, you’ll learn more about data engineering languages. Data specialists and data engineers must understand at least a few data programming languages depending on the scope of their work. Some of these languages are SQL, Java, XML, Python, and R. Understanding these languages helps data specialists understand data structures and architectures. It also helps them build succinct and integrated databases and data frameworks that move the needle for organizations. FREE ACCESS
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1mIn this video, you’ll summarize what you’ve learned. In this course, you’ve learned the difference between data, information, knowledge, and wisdom. You learned the main sources of data generation and some important data terminologies. You then discovered the three main types of data backup and the importance of data migration and data integration. You also defined data visualization and its importance and learned some important data engineering languages. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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