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BigDataAnalysen

BigDataAnalysen is the systematic process of collecting, cleaning, integrating, analyzing, and interpreting large-scale data sets to extract actionable insights. The term emphasizes both the scale of data and the analytical methods applied. In practice, BigDataAnalysen combine descriptive, diagnostic, predictive, and prescriptive analytics to support decision making, optimization, and innovation.

Data sources are heterogeneous, including transactional databases, log files, social media, sensor networks, images and videos,

Technologies include data storage in data lakes or data warehouses; distributed processing with frameworks such as

Governance and privacy are essential, covering data quality, lineage, metadata management, security, and compliance with regulations

Challenges include data quality and integration, interoperability, storage and compute costs, talent shortages, latency, and ensuring

Applications span finance, marketing, manufacturing, healthcare, public sector, and research, including fraud detection, customer segmentation, predictive

The field is evolving toward lakehouse architectures, data meshes, real-time analytics, and AI-assisted analysis, with increasing

and
external
data
such
as
weather
or
economic
indicators.
Hadoop
and
Spark;
streaming
with
Kafka
or
Flink;
and
query
engines
that
support
SQL
and
analytics.
such
as
GDPR
or
HIPAA.
reproducibility.
maintenance,
and
risk
analysis.
focus
on
automation,
data
governance,
and
privacy-by-design.