Навчальні курси Data Integration

Pentaho Data Integration is an open-source data integration tool for defining jobs and data transformations.

In this instructor-led, live training, participants will learn how to use Pentaho Data Integration's powerful ETL capabilities and rich GUI to manage an entire big data lifecycle and maximize the value of data within their organization.

By the end of this training, participants will be able to:

- Create, preview, and run basic data transformations containing steps and hops
- Configure and secure the Pentaho Enterprise Repository
- Harness disparate sources of data and generate a single, unified version of the truth in an analytics-ready format.
- Provide results to third-part applications for further processing

Audience

- Data Analyst
- ETL developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Pentaho Open Source BI Suite Community Edition (CE) is a business intelligence package that provides data integration, reporting, dashboards, and load capabilities.

In this instructor-led, live training, participants will learn how to maximize the features of Pentaho Open Source BI Suite Community Edition (CE).

By the end of this training, participants will be able to:

- Install and configure Pentaho Open Source BI Suite Community Edition (CE)
- Understand the fundamentals of Pentaho CE tools and their features
- Build reports using Pentaho CE
- Integrate third party data into Pentaho CE
- Work with big data and analytics in Pentaho CE

Audience

- Programmers
- BI Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Note

- To request a customized training for this course, please contact us to arrange.

KNIME Analytics Platform is a leading open source option for data-driven innovation, helping you discover the potential hidden in your data, mine for fresh insights, or predict new futures. With more than 1000 modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and the widest choice of advanced algorithms available, KNIME Analytics Platform is the perfect toolbox for any data scientist and business analyst.

This course for KNIME Analytics Platform is an ideal opportunity for beginners, advanced users and KNIME experts to be introduced to KNIME, to learn how to use it more effectively, and how to create clear, comprehensive reports based on KNIME workflows

KNIME is a free and open-source data analytics, reporting and integration platform. KNIME integrates various components for machine learning and data mining through its modular data pipelining concept. A graphical user interface and use of JDBC allows assembly of nodes blending different data sources, including preprocessing (ETL: Extraction, Transformation, Loading), for modeling, data analysis and visualization without, or with only minimal, programming. To some extent as advanced analytics tool KNIME can be considered as a SAS alternative.

Since 2006, KNIME has been used in pharmaceutical research, it also used in other areas like CRM customer data analysis, business intelligence and financial data analysis.

Sensor Fusion is the combination and integration of data from multiple sensors to provide a more accurate, reliable and contextual view of data.

Sensor Fusion implementations require algorithms to filter and integrate different data sources.

Audience

This course is targeted at engineers, programmers and architects who deal with multi-sensor implementations.

In this instructor-led, live training in україні, participants will learn how to use Talend Open Studio for ESB to create, connect, mediate and manage services and their interactions.

By the end of this training, participants will be able to

- Integrate, enhance and deliver ESB technologies as single packages in a variety of deployment environments.
- Understand and utilize Talend Open Studio's most used components.
- Integrate any application, database, API, or Web services.
- Seamlessly integrate heterogeneous systems and applications.
- Embed existing Java code libraries to extend projects.
- Leverage community components and code to extend projects.
- Rapidly integrate systems, applications and data sources within a drag-and-drop Eclipse environment.
- Reduce development time and maintenance costs by generating optimized, reusable code.

This instructor-led, live training in україні (online or onsite) is aimed at technical persons who wish to deploy Talend Open Studio for Big Data to simplifying the process of reading and crunching through Big Data.

By the end of this training, participants will be able to:

- Install and configure Talend Open Studio for Big Data.
- Connect with Big Data systems such as Cloudera, HortonWorks, MapR, Amazon EMR and Apache.
- Understand and set up Open Studio's big data components and connectors.
- Configure parameters to automatically generate MapReduce code.
- Use Open Studio's drag-and-drop interface to run Hadoop jobs.
- Prototype big data pipelines.
- Automate big data integration projects.

This instructor-led, live training in україні (online or onsite) is aimed at system administrators, data scientists, and business analysts who wish to set up Talend Administration Center to deploy and manage the organization's roles and tasks.

By the end of this training, participants will be able to:

- Install and configure Talend Administration Center.
- Understand and implement Talend management fundamentals.
- Build, deploy, and run business projects or tasks in Talend.
- Monitor the security of datasets and develop business routines based on the TAC framework.
- Obtain a broader comprehension of big data applications.

This instructor-led, live training in україні (online or onsite) is aimed at data administrators and developers who wish to manage, monitor, and operate data integration processes using Talend Cloud services.

By the end of this training, participants will be able to:

- Navigate the Talend Management Console to manage users and roles in the platform.
- Evaluate data to find and understand relevant datasets.
- Create a pipeline to process and monitor data at rest or in action.
- Prepare data for analysis to generate insights relevant to the business.