CertPath
📊 DataEntry → Advanced
📊

Data Analytics & Engineering Path

From data analyst to data engineer

The credential path for data careers — starting with analysis fundamentals and progressing through business intelligence, cloud data platforms, and professional data engineering.

Data AnalystBusiness Intelligence AnalystBI DeveloperData EngineerAnalytics Engineer
Total Cost
$800–$1,200
all materials included
Timeline
14–22 months
at 1–2 hrs/day
Exam Fees Only
$399
required certs
Steps
4 certifications
2 required, 2 optional

The Path

1
Required4–6 months

Google Data Analytics

Google Data Analytics Professional Certificate

Google's entry-level data analytics career credential — no experience required

$234

exam fee

Why at this step: Google's professional certificate covers the full data analysis workflow: data collection, SQL, data cleaning, analysis, visualization, and presentation. Widely recognized and a strong entry signal for analyst roles.

View full details →~180 study hours
2
Required2–3 months

PL-300

Microsoft Power BI Data Analyst

The leading business intelligence certification for Power BI professionals

$165

exam fee

Why at this step: Power BI is the dominant BI tool in enterprise environments. PL-300 proves you can build production-grade reports and dashboards — a core skill for analyst and BI developer roles at most companies.

View full details →~80 study hours
3
Optional2–3 months

SnowPro Core

SnowPro Core Certification

The essential Snowflake Data Cloud certification

$175

exam fee

Why at this step: Snowflake is the most widely adopted cloud data warehouse. SnowPro Core proves you can manage data at cloud scale — a key transition point from analyst to data engineer.

View full details →~60 study hours
4
Optional4–6 months

GCP Data Engineer

Google Cloud Professional Data Engineer

The top credential for cloud data pipeline and BigQuery expertise

$200

exam fee

Why at this step: GCP's Professional Data Engineer is one of the most rigorous data engineering credentials available. Targets senior data engineering roles building large-scale data pipelines and ML-ready infrastructure.

View full details →~120 study hours

Where to Specialize Next

After completing this path, these are the most popular specializations.

Machine Learning Track

Add ML engineering credentials to your data background.

Cloud Platform Depth

Go deep on your primary cloud data platform.

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