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PL-300T00: Microsoft Power BI Data Analyst

Nauji mokymai!

Trukmė Kalba Miestas Kaina Datos Registacija
3 dienos lietuvių - english - 1200 Eur - Teirautis
Datos -
Trukmė 3 dienos
Kalba lietuvių - english
Miestas -
Kaina 1200 Eur
Teirautis

Aprašymas

This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

Lektorius

Žilvinas Kundrotas – IT specialistas, daugiau nei 20 metų dirbęs inžinieriumi, konsultantu, instruktoriumi ir projektų vadovu programavimo ir sistemų administravimo srityse. Žilvinas jau daug metų dirba su Microsoft sprendimais tiek „on-premises“, tiek debesų sprendimais. Tai apima tokius produktus, kaip Microsoft SQL server, Azure Data Factory, PowerBI, Azure SQL server, Synapse Analytics.

Žilvinas dirba UAB „Fortevento” ir yra atsakingas už sprendimus duomenų apdorojimo srityje – vartotojų konsultavimą, jų poreikių analizę, sprendimų projektavimą ir įgyvendinimą, todėl tikrai padės susigaudyti smarkiai besiplečiančiame duomenų apdorojimo pasaulyje.

Lektorius Baltijos kompiuterių akademijoje yra sėkmingai pravedęs daugiau nei 20 kursų, turi sukaupęs didelę dėstymo patirtį, geba sudominti dalyvius ir konkrečiai bei aiškiai išdėstyti reikalingą medžiagą.

Štai kaip Žilviną vertina vienas iš mokymų dalyvių:

„Kursai buvo labai informatyvūs ir profesionalūs, jų metu gavau daug vertingos informacijos, kurią galėsime panaudoti praktiškai. Ačiū.“

Valdas B.

Kursai skirti

The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.

Kurso nauda

In this course students will learn:

  • Ingest, clean, and transform data
  • Model data for performance and scalability
  • Design and create reports for data analysis
  • Apply and perform advanced report analytics
  • Manage and share report assets

 

Programa

  1. Get Started with Microsoft Data Analytics
  2. Getting Data in Power BI
  3. Cleaning, Transforming, and Loading Data in Power BI
  4. Design a Data Model in Power BI
  5. Create Model Calculations using DAX in Power BI
  6. Optimize Model Performance in Power BI
  7. Create Reports in Power BI
  8. Create Dashboards in Power BI
  9. Identify Patterns and Trends in Power BI
  10. Create and Manage Workspaces in Power BI
  11. Manage Files and Datasets in Power BI
  12. Row-level Security in Power BI

Detali programa

 

Reikalavimai klausytojams

Successful Data Analysts start this role with experience of working with data in the cloud.

Specifically:

  • Understanding core data concepts.
  • Knowledge of working with relational data in the cloud.
  • Knowledge of working with non-relational data in the cloud.
  • Knowledge of data analysis and visualization concepts.

You can gain the prerequisites and a better understanding of working with data in Azure by completing Microsoft Azure Data Fundamentals before taking this course.

Module 1: Introduction to Azure Machine Learning
Getting Started with Azure Machine Learning
Azure Machine Learning Tools
Lab : Creating an Azure Machine Learning Workspace
Lab : Working with Azure Machine Learning Tools
Module 2: No-Code Machine Learning with Designer
Training Models with Designer
Publishing Models with Designer
Lab : Creating a Training Pipeline with the Azure ML Designer
Lab : Deploying a Service with the Azure ML Designer
Module 3: Running Experiments and Training Models
Introduction to Experiments
Training and Registering Models
Lab : Running Experiments
Lab : Training and Registering Models
Module 4: Working with Data
Working with Datastores
Working with Datasets
Lab : Working with Datastores
Lab : Working with Datasets
Module 5: Compute Contexts
Working with Environments
Working with Compute Targets
Lab : Working with Environments
Lab : Working with Compute Targets
Module 6: Orchestrating Operations with Pipelines
Introduction to Pipelines
Publishing and Running Pipelines
Lab : Creating a Pipeline
Lab : Publishing a Pipeline
Module 7: Deploying and Consuming Models
Real-time Inferencing
Batch Inferencing
Lab : Creating a Real-time Inferencing Service
Lab : Creating a Batch Inferencing Service
Module 8: Training Optimal Models
Hyperparameter Tuning
Automated Machine Learning
Lab : Tuning Hyperparameters
Lab : Using Automated Machine Learning
Module 9: Interpreting Models
Introduction to Model Interpretation
using Model Explainers
Lab : Reviewing Automated Machine Learning Explanations
Lab : Interpreting Models
Module 10: Monitoring Models
Monitoring Models with Application Insights
Monitoring Data Drift
Lab : Monitoring a Model with Application Insights
Lab : Monitoring Data Drift

Teirautis

PL-300T00: Microsoft Power BI Data Analyst
3 dienos
lietuvių - english
1200 Eur
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