Szkolenia Data Warehouse w Łódź

Azure Data Lake Storage Gen2 is a comprehensive and highly scalable data storage service offered by Microsoft Azure that provides a platform for analytics workloads.This instructor-led, live training (online or onsite) is aimed at intermediate-level data engineers who wish to learn how to use Azure Data Lake Storage Gen2 for effective data analytics solutions.By the end of this training, participants will be able to:

• Understand the architecture and key features of Azure Data Lake Storage Gen2.
• Optimize data storage and access for cost and performance.
• Integrate Azure Data Lake Storage Gen2 with other Azure services for analytics and data processing.
• Develop solutions using the Azure Data Lake Storage Gen2 API.
• Troubleshoot common issues and optimize storage strategies.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

IBM DataStage is a powerful extract, transform, load (ETL) tool used in data warehousing and business intelligence that helps organizations integrate and transform large volumes of data, from various data sources, into a unified format.This instructor-led, live training (online or onsite) is aimed at intermediate-level IT professionals who wish to have a comprehensive understanding of IBM DataStage from both an administrative and a development perspective, allowing them to manage and utilize this tool effectively in their respective workplaces.By the end of this training, participants will be able to:

• Understand the core concepts of DataStage.
• Learn how to effectively install, configure, and manage DataStage environments.
• Connect to various data sources and extract data efficiently from databases, flat files, and external sources.
• Implement effective data loading techniques.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Apache Kylin is an extreme, distributed analytics engine for big data. In this instructor-led live training, participants will learn how to use Apache Kylin to set up a real-time data warehouse. By the end of this training, participants will be able to:

• Consume real-time streaming data using Kylin
• Utilize Apache Kylin's powerful features, rich SQL interface, spark cubing and subsecond query latency

Note

• We use the latest version of Kylin (as of this writing, Apache Kylin v2.0)

Audience

• Big data engineers
• Big Data analysts

Format of the course

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

Amazon Redshift is a petabyte-scale cloud-based data warehouse service in AWS. In this instructor-led, live training, participants will learn the fundamentals of Amazon Redshift. By the end of this training, participants will be able to:

• Install and configure Amazon Redshift
• Load, configure, deploy, query, and visualize data with Amazon Redshift

Audience

• Developers
• IT Professionals

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.

The course is part of the Data Scientist skill set (Domain: Data and Technology).

Apache Druid is an open-source, column-oriented, distributed data store written in Java. It was designed to quickly ingest massive quantities of event data and execute low-latency OLAP queries on that data. Druid is commonly used in business intelligence applications to analyze high volumes of real-time and historical data. It is also well suited for powering fast, interactive, analytic dashboards for end-users. Druid is used by companies such as Alibaba, Airbnb, Cisco, eBay, Netflix, Paypal, and Yahoo. In this instructor-led, live course we explore some of the limitations of data warehouse solutions and discuss how Druid can compliment those technologies to form a flexible and scalable streaming analytics stack. We walk through many examples, offering participants the chance to implement and test Druid-based solutions in a lab environment.

Format of the Course

• Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding

Pivotal Greenplum is a Massively Parallel Processing (MPP) Data Warehouse platform based on PostgreSQL. This instructor-led, live training (online or onsite) is aimed at developers who wish to set up a multi-node Greenplum database. By the end of this training, participants will be able to:

• Install and configure Pivotal Greenplum.
• Model data in accordance to current needs and future expansion plans.
• Carry out different techniques for distributing data across multiple nodes.
• Improve database performance through tuning.
• Monitor and troubleshoot a Greenplum database.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Greenplum Database is a database software for business intelligence and data warehousing. Users can run Greenplum Database for massive parallel data processing. This instructor-led, live training (online or onsite) is aimed at administrators who wish to set up Greenplum Database for business intelligence and data warehousing solutions. By the end of this training, participants will be able to:

• Address processing needs with Greenplum.
• Perform ETL operations for data processing.
• Leverage existing query processing infrastructures.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

MemSQL is an in-memory, distributed, SQL database management system for cloud and on-premises. It's a real-time data warehouse that immediately delivers insights from live and historical data. In this instructor-led, live training, participants will learn the essentials of MemSQL for development and administration. By the end of this training, participants will be able to:

• Understand the key concepts and characteristics of MemSQL
• Install, design, maintain, and operate MemSQL
• Optimize schemas in MemSQL
• Improve queries in MemSQL
• Benchmark performance in MemSQL
• Build real-time data applications using MemSQL

Audience

• Developers
• Administrators
• Operation Engineers

Format of the course

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

Snowflake to platforma przechowywania danych w chmurze, która oferuje szerokie możliwości przetwarzania i analizy dużych zbiorów danych. Jest to rozwiązanie typu Software-as-a-Service (SaaS), które łączy w sobie elastyczność i skalowalność chmury z możliwościami zaawansowanego magazynu danych. Kluczowe cechy i funkcje Snowflake obejmują:Architektura oparta na chmurze: Snowflake jest zbudowany w chmurze i zoptymalizowany pod kątem elastyczności i wydajności, co pozwala na łatwą skalowalność zasobów do przechowywania i przetwarzania danych.Rozdzielenie obciążenia magazynowania i przetwarzania: Unikalna architektura Snowflake rozdziela obciążenie magazynowania danych od obciążenia przetwarzania, co pozwala na niezależne skalowanie i optymalizację tych dwóch aspektów.Wsparcie dla różnorodnych danych: Snowflake umożliwia przechowywanie i analizę różnorodnych typów danych, w tym danych strukturalnych, półstrukturalnych (np. JSON, XML) i niestrukturalnych.Wysoka wydajność i optymalizacja zapytań: System oferuje szybkie przetwarzanie zapytań i automatyczną optymalizację, co pozwala na efektywne wykonywanie złożonych analiz na dużych zbiorach danych.Zabezpieczenia i zarządzanie dostępem: Snowflake zapewnia zaawansowane funkcje bezpieczeństwa, w tym szyfrowanie danych, zarządzanie dostępem na poziomie ról i audytowanie.Łatwość integracji: Platforma łatwo integruje się z popularnymi narzędziami i usługami ETL, BI oraz analizy danych, co pozwala na tworzenie kompleksowych rozwiązań analitycznych.Elastyczność i skalowalność kosztów: Model płatności oparty na użyciu pozwala na optymalizację kosztów i płacenie tylko za faktycznie wykorzystane zasoby.Uniwersalność zastosowań: Snowflake jest odpowiedni dla różnych przypadków użycia, od prostych analiz BI po zaawansowane przetwarzanie danych, w tym analizy big data, machine learning i inne.

Data Vault Modeling is a database modeling technique that provides long-term historical storage of data that originates from multiple sources. A data vault stores a single version of the facts, or "all the data, all the time". Its flexible, scalable, consistent and adaptable design encompasses the best aspects of 3rd normal form (3NF) and star schema. In this instructor-led, live training, participants will learn how to build a Data Vault. By the end of this training, participants will be able to:

• Understand the architecture and design concepts behind Data Vault 2.0, and its interaction with Big Data, NoSQL and AI.
• Use data vaulting techniques to enable auditing, tracing, and inspection of historical data in a data warehouse.
• Develop a consistent and repeatable ETL (Extract, Transform, Load) process.
• Build and deploy highly scalable and repeatable warehouses.

Format of the course

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