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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 : Daniel Pham
IBM Knowledge Catalog on Cloud Pak for Data (CP4D)...
4.8 398
13 lectures All Level
By : ajmal ali
Mastering the JOIN operation for Data Analysis...
4.3 739
5 lectures All Level
By : Yoann Bierling
Unlock the Power of Clean Data with SAP...
4.8 763
1:35:45 hrs 16 lectures All Level
By : Daniel Pham
Unlock the Power of Data Integration (ETL): Practical Training with IBM DataStage (ET...
4.5 1278
8:1:57 hrs 273 lectures All Level
By : Daniel Pham
Comprehensive ETL, Data Integration and Change Data Capture (Oracle Golden Gate)...
4.5 649
3:50:55 hrs 62 lectures All Level
By : Daniel Pham
Modernizing Data Warehousing with Data Vault 2.0 Methodology...
4.5 684
59 lectures All Level
By : RougeNeuron Academy
Debugging is identifying the root cause of an unexpected behavior in a software syste...
4 620
28 lectures All Level
By : Amit Ranjan
Get to hands on from the first hour and travel through the concepts and details to em...
4.6 71065
2:43:11 hrs 14 lectures Intermedite Level
By : Amit Ranjan
In-Depth, Hands-On driven exposure to the features and concpets of Spark Core with ti...
4.8 85136
10:38:59 hrs 31 lectures Intermedite Level
By : Navdeep Kaur
Complete course on Sqoop, Flume & Hive- Great for CCA175 & Hortonwork Spark Certifica...
4.3 83261
5:47:17 hrs 70 lectures Intermedite 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.