AI & Data

Power BI and SQL Database Training

This training is intended for people working with processing and analyzing large amounts of data, including analysts and decision-makers using SQL database data.

Duration
6h
Ask about the program → See all
Who it's for

Ideal for teams that…

1 Analysts, marketers, and everyone working with data
2 People processing and analyzing large datasets
3 Those who want to learn the DAX library
Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

Efficiently acquire and process data for business decision-making

✓

Use PowerQuery and data preparation techniques

✓

Learn the terminology and tools necessary for extracting information from SQL databases and presenting it in Power BI

✓

Apply the DAX library for reporting and analysis

✓

Tell stories with data using visualization techniques

Program · 16 modules

What we actually do

M01
Introduction to the Program
  • · Versions, license types, and features
  • · Main applications and user interface overview
  • · Reports, cards, and visualizations – key Power BI elements
  • · Cloud Power BI services – capabilities and limitations
M02
First Power BI Model
  • · Working with a single-table data model
  • · Basic visualizations and binding data to visuals
  • · Data types, conversions, and regional settings
  • · Line, bar, and scatter charts – formatting
  • · Card, table, and matrix visuals – formatting
  • · Geographic visualizations – maps and choropleths
  • · Visualization, card, and report-level filters
M03
Working with Multi-Table Models
  • · Tables, relationships, and data models
  • · Automatic and manual relationships
  • · Model optimization and modification
  • · Calculated columns and KPIs
  • · Introduction to data modeling and joins
M04
Power Query Data Model for Power BI Desktop
  • · Data source types – capabilities and limitations
  • · Flat files (CSV, JSON) and folder-based sources
  • · Spreadsheet data as a visualization source
  • · Combining custom data sources: SQL, CSV, Web
M05
Advanced Visual Elements
  • · Key Performance Indicators (KPIs)
  • · Advanced hierarchies in data models
  • · Custom visuals from marketplace and files
M06
Sharing Power BI Desktop Reports
  • · Exporting data to CSV
  • · Exporting reports to PDF
  • · Publishing reports to the cloud
  • · Embedding reports in SharePoint and public websites
M07
Data Processing Stages in Power BI
  • · SQL query execution
  • · Data transformation using M language
  • · DAX processing layer
M08
SQL Databases – Introduction and Overview
  • · SQL database concepts
  • · SQL language categories: DQL, DML, DDL, DCL
  • · Connecting to SQL servers and databases
  • · SQL editors and development tools
  • · Server objects: tables, views, stored procedures
M09
Connecting Power BI to a Database
  • · Direct database connections
  • · ODBC connections
  • · Loading data from tables and views
M10
Power Query for Data Transformation
  • · Filtering and sorting data
  • · Calculated and conditional columns
  • · Custom column creation
  • · Text and mathematical functions
  • · Data type conversions
  • · Merging and splitting columns
M11
Data Model and M Language
  • · Appending and merging tables
  • · Relationships and Excel-based models
  • · Advanced M language functions
  • · Removing duplicates
  • · Pivot and unpivot operations
  • · Aggregations and counts
M12
Practical Aspects of the Data Model
  • · Pivot tables based on the data model
  • · Multiple object references
  • · Data refresh mechanisms
M13
Introduction to DAX
  • · What DAX is and where it is used
  • · Requirements and prerequisites
  • · Work environment: formula bar and calculation area
M14
Working with DAX
  • · DAX syntax
  • · Calculated columns and use cases
  • · Formula structure and formatting
  • · Measures in DAX
  • · Auto-sum functionality
  • · Functions and function types
  • · RELATED and relationship functions
  • · Row context and filter context
M15
DQL – Data Query Language
  • · Using Query Designer
  • · SQL data types and usage
  • · SQL data standards
M16
SELECT Statement
  • · SELECT statement syntax
  • · Logical execution order of SELECT
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

Ochrona antyspamowa (Cloudflare Turnstile) zostanie aktywowana po wpięciu klucza.

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