What is Big Data?
Turkish: Big Data
Big data is the practice of processing and analyzing datasets whose volume, speed, or variety exceeds traditional tools.
What is Big Data?
Big data is an approach for working with data whose volume, speed, or variety is difficult for traditional databases and reporting tools to handle comfortably. The “big” part is not only about terabytes; fast event streams or mixed unstructured logs, text, and records can also create big data needs.
Core Characteristics
Big data is often described through the 3Vs: volume, velocity, and variety. Some projects also consider validity, value, or variability. Data may arrive as files, event streams, logs, sensor readings, transaction records, or user behavior.
Architectures may use data lakes, distributed processing, queues or stream infrastructure, columnar storage, and analytics engines. Batch and real-time processing needs should be designed separately.
Business Use
Retail demand forecasting, financial risk analysis, manufacturing sensors, web behavior analytics, fraud detection, and customer segmentation are common big data examples. ETL is the process of transforming and loading data; a data pipeline manages reliable movement from source systems to target systems.
The biggest risk in a big data project is building the technology stack before the business question is clear. Decision needs, data quality, and operating cost should be defined first.
Related Terms
BI turns company data into reports, dashboards, and analysis models that make decision-making processes visible.
Data LakeA data lake stores raw and processed data in scalable storage for analytics, machine learning, exploration, and archiving.
Data PipelineA data pipeline collects, cleans, transforms, and moves data from sources to a target system for reporting or analytics.
ETL (Extract, Transform, Load)ETL extracts data from multiple sources, transforms it, and loads it into a data warehouse or reporting system on a schedule.
Process MiningProcess mining analyzes ERP, CRM, and workflow logs to reveal real process paths, bottlenecks, rework, and deviations from the intended flow.