Pentaho Business Intelligence (PBI) - moduły raportowe Training Course

Knowledge discovery in databases (KDD) is the process of discovering useful knowledge from a collection of data. Real-life applications for this data mining technique include marketing, fraud detection, telecommunication and manufacturing.

In this instructor-led, live course, we introduce the processes involved in KDD and carry out a series of exercises to practice the implementation of those processes.

Audience

• Data analysts or anyone interested in learning how to interpret data to solve problems

Format of the Course

• After a theoretical discussion of KDD, the instructor will present real-life cases which call for the application of KDD to solve a problem. Participants will prepare, select and cleanse sample data sets and use their prior knowledge about the data to propose solutions based on the results of their observations.

The "Pentaho Data Integration (PDI) - moduł do przetwarzania danych ETL (poziom średniozaawansowany)" training provides knowledge about the Pentaho platform, which covers the area of Business Intelligence, reporting, data analysis and data integration. Participants will acquire skills in installing, configuring and working with Pentaho Data Integration, learning how to create transformations, work with databases, filter and group data, handle XLS files, define parameters and variables. The training also covers advanced topics such as data versioning, database transactions, the use of JavaScript, task scheduling and running transformations in parallel.

The "Pentaho Data Integration (PDI) - ETL data processing module" training offers advanced knowledge of the Pentaho platform, covering the area of Business Intelligence, reporting, data analysis and data integration. It is addressed to programmers, architects and application administrators, enabling learning how to design, implement, monitor and optimize ETL processes using Pentaho Data Integration (PDI). Participants will gain skills in working with various types of data, filtering, grouping and combining data, as well as scheduling tasks, running transformations and creating clusters. The training also covers advanced topics such as data versioning, database transactions, JavaScript usage, mapping transformations, data type conversion and remote launch.

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.

Goal:

Learning to work with SPSS at the level of independence

The addressees:

Analysts, researchers, scientists, students and all those who want to acquire the ability to use SPSS package and learn popular data mining techniques.

Course can be provided with any tools, including free open-source data mining software and applications

Audience

If you try to make sense out of the data you have access to or want to analyse unstructured data available on the net (like Twitter, Linked in, etc...) this course is for you.

It is mostly aimed at decision makers and people who need to choose what data is worth collecting and what is worth analyzing.

It is not aimed at people configuring the solution, those people will benefit from the big picture though.

Delivery Mode

During the course delegates will be presented with working examples of mostly open source technologies.

Short lectures will be followed by presentation and simple exercises by the participants

Content and Software used

All software used is updated each time the course is run, so we check the newest versions possible.

It covers the process from obtaining, formatting, processing and analysing the data, to explain how to automate decision making process with machine learning.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.

The objective of the course is to enable participants to gain a mastery of how to work with the SQL language in Oracle database for data extraction at intermediate level.

Objective:

Delegates be able to analyse big data sets, extract patterns, choose the right variable impacting the results so that a new model is forecasted with predictive results.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has also found followers among statisticians, engineers and scientists without computer programming skills who find it easy to use. Its popularity is due to the increasing use of data mining for various goals such as set ad prices, find new drugs more quickly or fine-tune financial models. R has a wide variety of packages for data mining.

R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.

This course is intended for engineers and decision makers working in data mining and knoweldge discovery.

You will learn how to create effective plots and ways to present and represent your data in a way that will appeal to the decision makers and help them to understand hidden information.

Big data is data sets that are so voluminous and complex that traditional data processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.