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Intelligence View

⚡ tsecurity.de Intelligence

# Getting Data from Different Sources in Power BI

Table of Contents Executive Introduction Key Objectives Power BI Data Architecture Connecting to Data Sources Data Quality Best Practices Conclusion Executive Introduction The foundation of every successful Power BI report…

Sichere Programmierung dev.to 30.03.2026, 13:42 Uhr 3 Min. Lesezeit KRITIS / Energie Cloud & IT-Enterprise

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Executive Introduction

Key Objectives

Power BI Data Architecture

Connecting to Data Sources

Data Quality Best Practices

Conclusion

Executive Introduction

The foundation of every successful Power BI report is reliable data ingestion. Regardless of how visually compelling a dashboard may be, insights are only as strong as the quality, completeness, and integrity of the underlying data.

In modern business environments, data rarely resides in a single location. Organizations operate across diverse systems—spreadsheets, databases, cloud platforms, APIs, and document repositories. Power BI is designed to seamlessly integrate these environments through its powerful data connectivity framework and Power Query transformation engine.

Key Objectives

Connect Power BI to multiple data sources efficiently.

Explore data structures using Power Query.

Detect and resolve data quality issues early.

Establish a scalable foundation for accurate reporting.

Power BI Data Architecture Overview

At a high level, the Power BI data architecture consists of three major layers:

Data Sources: Excel, SQL Server, MySQL, JSON APIs, SharePoint, etc.

Power Query (ETL Layer): Extraction, transformation, cleansing, and validation.

Data Model & Reporting Layer: Relationships, DAX calculations, and visuals.

All data flows through Power Query before entering the data model to ensure consistency and quality control.

Connecting to Multiple Data Sources

Most connectors follow a similar workflow. Click below to see the specific steps for each source:

File-Based Sources

Excel, CSV, or PDF

Navigate to Home → Get Data.

Select the specific file type (Excel, Text/CSV, or PDF).

Authenticate/Select the file.

Preview data in the Navigator window.

Choose Transform Data.

Databases

SQL Server or MySQL

Navigate to Home → Get Data.

Select the database engine.

Enter Server/Database credentials.

Choose between Import or DirectQuery.

Select tables and click Transform Data.

Cloud & API Sources

SharePoint, JSON APIs, or Azure

Navigate to Home → Get Data.

Select the appropriate Web or Cloud connector.

Paste the URL or API endpoint.

Preview the schema and click Transform Data.

Data Quality and Preparation Best Practices

Review Data Types: Check column types immediately after loading.

Handle Nulls: Check for missing values that could skew averages.

Standardize: Ensure date formats and naming conventions are consistent.

Validate: Match row counts against your source systems.

Architecture Diagram Overview

The Visual Flow

Data Sources (Left) → Power Query ETL (Middle) → Data Model & Reports (Right)

(Note: If you have an image for this, use the syntax below:)

Conclusion

Connecting to multiple data sources is the strategic foundation of reliable analytics. Effective data ingestion enables accurate insights and confident decision-making. Great analytics begins with great data—and great data begins with disciplined ingestion and transformation

IR-PLAYBOOK-RCEHIGH

Schritte anzeigen

SOC Incident Playbook: Remote Code Execution (RCE) Defense

WAF MitigationSofort

Virtuelles Patchen am Reverse Proxy / WAF für gefährdete URL-Pfade und Payloads aktivieren.

SecRule REQUEST_URI "@rx ..." "id:1001,phase:1,deny,status:403"

Web Shell ScanSofort

Web-Root auf neu angelegte Scripts, anomal modifizierte Dateien und Persistence scannen.

find /var/www -type f -name "*.php" -mmin -120

Outbound FilteringSofort

Ausgehenden Datenverkehr (Reverse Shells zu unbekannten IPs/Ports) blockieren.

ss -tunp | grep -E ":(4444|1337|8080|9001)"

Vendor Patching

Hersteller-Update in Staging validieren und schnellstmöglich in Produktion ausrollen.

apt update && apt --only-upgrade install <pkg>

1-Click Detection Engineering: Multi-Dialect SIEM Rules5 Formate

Regeln anzeigen

Syntax validiert (0 Fehler)

title: Detect Exploitation - # Getting Data from Different Sources in Power BI
id: 3b3332d0-fe53-441d-80fa-aedcc159aff4
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access

Syntax validiert (0 Fehler)

rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "# Getting Data from Different " ascii wide
    condition:
        any of them
}

Syntax validiert (0 Fehler)

index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("Getting Data from Different Sources in P")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count

Syntax validiert (0 Fehler)

message: "*Getting Data from Different Sources in P*"

Syntax validiert (0 Fehler)

CommonSecurityLog
| where Message has "Getting Data from Different Sources in P"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

🎯

MITRE ATT&CK Matrix Navigator 14 Taktiken

Reconnaissance

Resource Development

Initial Access

Execution

Persistence

Privilege Escalation

Defense Evasion

Credential Access

Discovery

Lateral Movement

Collection

Command and Control

Exfiltration

Impact

💡 Tipp: Klicken Sie auf eine TTP, um Gegenmaßnahmen und SIEM-Erkennungsregeln anzuzeigen.Enterprise Matrix v14.1

🚀 Auf tsecurity.de entdecken

◀ VORHERIGER BEITRAG 1 Min

USN-8129-1: pyasn1 vulnerability

Unix & Linux Server

NÄCHSTER BEITRAG 1 Min

Apple M4 und M5: Einschränkungen bei 4K-Displays sorgen für Kritik

Apple iOS & macOSWeiterlesen ▶

Blättern: Pfeiltasten [ ← ] [ → ] · Tasten j / k · mobil: Wischen

Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich # Getting Data from Different Sources in.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen

1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.

🔗 Semantisch verwandte Zero-Days MariaDB 11.7 VEC

Schnell-Prompts für Analysten

⚠️ DEFANGED SANDBOX VIEW (tsecurity.de): Alle Netzwerkindikatoren und URLs wurden neutralisiert (2 Indikatoren entschärft). Nur zur defensiven Analyse!

Format: python

#!/usr/bin/env python3
# Exploit Title: PoC for Target
import socket, sys
target = '192[.]168[.]1[.]10'
url = 'hxxp://target[.]local/vuln'
s = socket.socket()
s.connect((target, 80))
s.send(b'GET / HTTP/1.1\r\nHost: target.local\r\n\r\n')