Big data analytics
Artificial Intelligence (AI), mobile, social and Internet of Things (IoT) are driving data complexity, new forms and sources of data. Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes. Analyzing big data allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or unusable. Using advanced analytics techniques such as text analytics, machine learning, predictive analytics, data mining, statistics, and natural language processing, businesses can analyze previously untapped data sources independent or together with their existing enterprise data to gain new insights resulting in better and faster decisions.
- Big data Hadoop
- Apache
- Scala
- Spark
Related Conference of Big data analytics
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Big data analytics Conference Speakers
Recommended Sessions
- Artificial intelligence
- Artificial intelligence applications
- Augmented reality (AR) and Virtual reality
- Big data
- Big data analytics
- Business Intelligence
- Cloud computing
- Cloud computing in E-commerce
- Computer Science and Technology
- Data analytics in cloud
- Data Mining
- Deep learning
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- Machine learning
- SAP SAS (Statistical Analysis System)
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- Water Resource Management - Civil Engineering 2020 (Netherlands)
- Wearable Biosensors - Biosensors & Bioelectronics 2020 (Canada)
- Wearables & Mobile Diagnostics - Microfluidics 2020 (Netherlands)
- Weather Satellites - Satellite 2020 (UK)
- Wind Energy - Renewable Energy 2020 (Canada)
- Wireless Communications - Satellite-2019 (Italy)