Source Data Integration (NL)

261548

What is Source Data Integration

With today's data abundance, gaining insights from data is an essential step for companies to make fact-based decisions. Business-related data is recorded in various source systems. By collecting data from different source systems and linking it to each other, interesting insights can arise. And in principle, the more data is collected, the more insights can be extracted.
Collecting and copying this source data is called Source Data Integration.
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.

Who should attend Source Data Integration

The Source Data Integration training is suitable for:

• Starters at the beginning of their career
• People making a career switch to Data Engineering
• People working in IT, especially in departments such as BI and DWH
• Business Analysts
• Information Analysts

Prerequisites

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

Objectives

After this training, the participant is able to answer the questions:

• When should a new source be integrated?
• What different delivery techniques and delivery methods are there?
• What is ETL?
• How to guarantee the completeness and correctness of source data?

Within the Source Data Integration course you will learn, among other things:

• The process in which, based on the information needs of customers, it is ascertained whether new data sources should be unlocked or expanded.
• The different delivery techniques with which data can be obtained from source systems. This includes file delivery, web-based delivery through an API, an export of a database table, the direct extraction of data from a source table or 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).
• The different delivery methods in which data can be delivered. You will be introduced to the full, incremental, stackable and event-driven delivery methods.
• How history of source data can be built up in a data warehouse. How the “deltas” or new and changed source data can be derived based on the delivery method.
• The agreements that must be made with the source to specify which data must be supplied, in which formats, with which delivery technique, method, frequency and times. You will learn the terms interface, metadata and Service Level Agreements (SLA).
• How and why the quality of the data delivery should be determined.
• The benefits of standardizing and reusing ETL jobs. How can these be made generic and metadata-driven?

261548

What is Source Data Integration

With today's data abundance, gaining insights from data is an essential step for companies to make fact-based decisions. Business-related data is recorded in various source systems. By collecting data from different source systems and linking it to each other, interesting insights can arise. And in principle, the more data is collected, the more insights can be extracted.
Collecting and copying this source data is called Source Data Integration.
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.

Who should attend Source Data Integration

The Source Data Integration training is suitable for:

• Starters at the beginning of their career
• People making a career switch to Data Engineering
• People working in IT, especially in departments such as BI and DWH
• Business Analysts
• Information Analysts

Prerequisites

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

Objectives

After this training, the participant is able to answer the questions:

• When should a new source be integrated?
• What different delivery techniques and delivery methods are there?
• What is ETL?
• How to guarantee the completeness and correctness of source data?

Within the Source Data Integration course you will learn, among other things:

• The process in which, based on the information needs of customers, it is ascertained whether new data sources should be unlocked or expanded.
• The different delivery techniques with which data can be obtained from source systems. This includes file delivery, web-based delivery through an API, an export of a database table, the direct extraction of data from a source table or 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).
• The different delivery methods in which data can be delivered. You will be introduced to the full, incremental, stackable and event-driven delivery methods.
• How history of source data can be built up in a data warehouse. How the “deltas” or new and changed source data can be derived based on the delivery method.
• The agreements that must be made with the source to specify which data must be supplied, in which formats, with which delivery technique, method, frequency and times. You will learn the terms interface, metadata and Service Level Agreements (SLA).
• How and why the quality of the data delivery should be determined.
• The benefits of standardizing and reusing ETL jobs. How can these be made generic and metadata-driven?