Big Data refers to extremely large datasets that cannot be processed or analyzed using traditional data management tools.
It involves:
Volume: The vast amount of data generated every second, including structured and unstructured data.
Variety: Different types of data from various sources such as social media, IoT, and transactional data.
Velocity: The speed at which data is generated and processed.
Veracity: The uncertainty and reliability of data.
Value: The insights and actionable information that can be extracted from Big Data for decision-making.
Tools: Technologies like Hadoop, Spark, and cloud computing are used for handling Big Data.
Here are some interesting seminar topics related to data mining: Introduction to Data Mining Techniques – Overview of fundamental techniques like classification, clustering, regression, and association rule mining. Applications of Data Mining in Healthcare – How data mining is transforming patient care, disease prediction, and medical research. Big Data and Data Mining – Integrating data mining with big data tools to extract valuable insights. Data Mining in E-commerce – Techniques for customer behavior analysis and recommendation systems. Machine Learning in Data Mining – Exploring the role of machine learning algorithms in enhancing data mining processes. Data Mining for Fraud Detection – Using data mining to identify fraudulent activities in banking and finance.
Data science is a process that uses data to generate insights that can be used to make decisions. Data analytics is a process that uses data to generate insights that can be used to make decisions. Big data is a collection of data that is too large to be processed by traditional methods.
Aggregate Data - it comes from multiple patients and are grouped together without the ability to identify the particular patient and is used for research, quality improvement activities and other statistical analyses.
Data collected on large populations and stored in databases is referred to as big data. This type of data is typically characterized by its volume, velocity, and variety, and requires specialized tools and techniques to analyze and derive insights from.
A "schema-on-read" database is one that allows users to define the structure of the data as they access it, rather than enforcing a predefined schema. This approach allows for flexibility in data organization and analysis, making it a popular choice for big data and analytics applications.
Big data refers to massive amounts of data on which technology can be applied. A data warehouse is a repository of historical data from a company's many operations. Big data is a method of storing and managing massive amounts of information. To learn more about data science please visit- Learnbay.co
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Big Data Training In Chennai provides real-time and placement-focused Big Data Training in chennai. Our ibm Big Data Hadoop training includes basic to advanced level and our Big Data Training course is planned to get placement in successful MNC companies in Chennai as soon as you complete the ibm Big Data Certification Course in our Big Data Hadoop Training Institute in Chennai.The big data coaches are ibm big data hadoop certified specialists with understanding of numerous big data projects and 9 years of experience working professionals and hands on real time. We have planned our curriculum and syllabus for Big Data course focused on student requirements to achieve the career target of everyone. The topics discussed in Chennai's big data qualification training include Presentation.Chennai provides Big Data training in Chennai with option of several training sites. Our Chennai hadoop-training institutes are fitted with laboratory equipment and excellent infrastructure. We also provide our students in Chennai with the training course of big data hadoop qualification. We have graduated more than 3075 students through our affiliated Big Data training centers and put 2277 students through our recruitment and placement programme.
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Big data analytics is the use of advanced analytic techniques to very large, heterogeneous data sets, which can contain structured, semi-structured, and unstructured data, as well as data from many sources and sizes ranging from terabytes to zettabytes. To learn more about data science please visit- Learnbay.co
Big Data refers to large volumes of structured and unstructured data that are too complex to be processed by traditional data management tools. It focuses on collecting, storing, and managing huge datasets. Data Science, on the other hand, involves analyzing and interpreting complex data to extract meaningful insights and support decision-making. It combines techniques from statistics, machine learning, and data analysis, often working with big data to derive actionable knowledge. In short, Big Data is about the data itself, while Data Science is about analyzing and making sense of that data.
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Big data is expected to be 7.9ZB in 2015. It is nothing but an assortment of such a huge and complex data that it becomes very tedious to capture, store, process, retrieve and analyze it with the help of on hand database management tools or traditional data processing techniques.
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