Source Data Integration (EN)

287560

What is Source Data Integration

In today’s data-rich environment, extracting insights from data is crucial for businesses to make informed decisions. Data related to business operations is recorded in various source systems. By collecting and linking data from these different source systems, we can derive valuable insights. The more data we collect, the more insights we can extract. This process of collecting and copying source data is known as Source Data Integration.
In this training, you will learn about:

• The process of determining whether new data sources should be unlocked or expanded based on customer information needs.
• Various data delivery techniques, including file delivery, web-based delivery through an API, database table exports, direct data extraction from a source table, and Change Data Capture (CDC).
• The technique with which data can be processed and stored in, for example, a data warehouse. You will be introduced to Extract, Transform and Load (ETL).
• Different data delivery methods, including full, incremental, stackable, and event-driven delivery methods.
• Building up the history of source data in a data warehouse and deriving “deltas” or new and changed source data based on the delivery method.
• The agreements that need to be made with the source to specify the data to be supplied, the formats, delivery technique, method, frequency, and times. You will learn about interfaces, metadata, and Service Level Agreements (SLA).
• Determining the quality of data delivery and why it’s important.
• The benefits of standardizing and reusing ETL jobs and how they can be made generic and metadata-driven.

During the training the application of what you learn is central and you are challenged to work with the given theory in practical cases. The training is given by people who work in practice within Data Engineering and know what it is about. They would like to transfer that practical knowledge.

Our trainers, with their wealth of practical experience, bring theoretical concepts to life by providing insights drawn from real-world scenarios and sharing best practices. This Source Data Integration training is designed to empower you with the necessary skills to adeptly navigate the intricate realm of data integration, thereby enabling you to extract maximum value from your organization’s data assets. This hands-on approach ensures that you are not just learning the concepts, but also understanding how to apply them in real-world situations to drive tangible results.

Who should attend Source Data Integration

• Data Engineers: Professionals who design, build, and manage the data infrastructure. They develop the architecture that helps analyze and process data in the way the organization needs it.
• Data Analysts: They manipulate large data sets and use them to identify trends and reach meaningful conclusions to inform strategic business decisions.
• Business Intelligence Professionals: They use data to help figure out market and business trends by analyzing data to develop a clearer picture of where the business stands.
• Data Science Managers: Professionals who oversee the data science team, guiding the raw data journey to useful insights.
• IT Managers: They are responsible for coordinating, planning, and leading computer-related activities in an organization.

Prerequisites

There are no specific requirements to participate in this training.
The use of a laptop is required for this training.

Objectives

At the end of the training, you will be able to:

• Determine when a new source should be integrated.
• Understand different delivery techniques and delivery methods.
• Understand what ETL is.
• Guarantee the completeness and correctness of source data.

287560

What is Source Data Integration

In today’s data-rich environment, extracting insights from data is crucial for businesses to make informed decisions. Data related to business operations is recorded in various source systems. By collecting and linking data from these different source systems, we can derive valuable insights. The more data we collect, the more insights we can extract. This process of collecting and copying source data is known as Source Data Integration.
In this training, you will learn about:

• The process of determining whether new data sources should be unlocked or expanded based on customer information needs.
• Various data delivery techniques, including file delivery, web-based delivery through an API, database table exports, direct data extraction from a source table, and Change Data Capture (CDC).
• The technique with which data can be processed and stored in, for example, a data warehouse. You will be introduced to Extract, Transform and Load (ETL).
• Different data delivery methods, including full, incremental, stackable, and event-driven delivery methods.
• Building up the history of source data in a data warehouse and deriving “deltas” or new and changed source data based on the delivery method.
• The agreements that need to be made with the source to specify the data to be supplied, the formats, delivery technique, method, frequency, and times. You will learn about interfaces, metadata, and Service Level Agreements (SLA).
• Determining the quality of data delivery and why it’s important.
• The benefits of standardizing and reusing ETL jobs and how they can be made generic and metadata-driven.

During the training the application of what you learn is central and you are challenged to work with the given theory in practical cases. The training is given by people who work in practice within Data Engineering and know what it is about. They would like to transfer that practical knowledge.

Our trainers, with their wealth of practical experience, bring theoretical concepts to life by providing insights drawn from real-world scenarios and sharing best practices. This Source Data Integration training is designed to empower you with the necessary skills to adeptly navigate the intricate realm of data integration, thereby enabling you to extract maximum value from your organization’s data assets. This hands-on approach ensures that you are not just learning the concepts, but also understanding how to apply them in real-world situations to drive tangible results.

Who should attend Source Data Integration

• Data Engineers: Professionals who design, build, and manage the data infrastructure. They develop the architecture that helps analyze and process data in the way the organization needs it.
• Data Analysts: They manipulate large data sets and use them to identify trends and reach meaningful conclusions to inform strategic business decisions.
• Business Intelligence Professionals: They use data to help figure out market and business trends by analyzing data to develop a clearer picture of where the business stands.
• Data Science Managers: Professionals who oversee the data science team, guiding the raw data journey to useful insights.
• IT Managers: They are responsible for coordinating, planning, and leading computer-related activities in an organization.

Prerequisites

There are no specific requirements to participate in this training.
The use of a laptop is required for this training.

Objectives

At the end of the training, you will be able to:

• Determine when a new source should be integrated.
• Understand different delivery techniques and delivery methods.
• Understand what ETL is.
• Guarantee the completeness and correctness of source data.