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What is big data? It's a phrase used to quantify data sets that are so large and complex that they become difficult to exchange, secure, and analyze with typical tools. These courses on big data show you how to solve these problems, and many more, with leading IT tools and techniques.
By : Navdeep Kaur
A complete guide for Cassandra architecture, Cassandra Query language ,Cluster manage...
4.8 93150
1:47:36 hrs 23 lectures Intermedite Level
By : Navdeep Kaur
Great for CCA 159 Preparation - Big Data Certification for Non Programmers,Business A...
4.6 94173
3:33:6 hrs 47 lectures Beginner Level
By : Manoj G T
Apache NiFi is a robust open-source Data Ingestion and Distribution framework and mor...
4.2 72983
1:23:18 hrs 19 lectures Beginner Level
By : Saheb Singh chaddha
Managing Big data using Hadoop tools like MapReduce, Hive, Pig, hBase and m...
4.1 34135
26 lectures Beginner Level
By : Eduardo Morelli
Use Big Data tools (R, RStudio, MongoDB, AzureML) to solve a real problem!...
4.6 5945
6 lectures Beginner Level
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Big Data refers to extremely large and complex data sets that exceed the capabilities of traditional data processing methods. It encompasses three main characteristics: volume (large amounts of data), velocity (rapid data generation or processing), and variety (diverse data types).
Key technologies in Big Data processing include Apache Hadoop, Apache Spark, Apache Flink, and distributed storage systems like HDFS (Hadoop Distributed File System). These technologies enable the storage, processing, and analysis of massive datasets.
Big Data analytics allows businesses to gain valuable insights from vast amounts of data. It facilitates data-driven decision-making by identifying patterns, trends, and correlations that can inform strategic planning, customer engagement, and operational efficiency.
Challenges in managing Big Data include scalability, data integration, security, and the need for specialized skills. Analyzing Big Data poses challenges related to extracting meaningful insights from diverse and unstructured data sources.
Big Data differs from traditional data processing in terms of scale, speed, and variety. Traditional data processing methods may struggle to handle the volume and speed of Big Data, and Big Data often involves diverse data types beyond the structured data typically handled in traditional databases.