Sentiment Analysis Sentiment Analysis is monitoring what consumers are saying about a company’s brands and products and how they are expressing their opinions and sentiments to others has always been important to businesses. Until the last century, businesses typically used surveys and focus groups from …
Data Mining Classification & Prediction Classification Classification involves dividing up objects so that each is assigned to one of a number of mutually exhaustive and exclusive categories known as classes. Many practical decision-making tasks can be formulated as classification problems. customers who are likely to …
Data Visualization Data visualization is the art and practice of gathering, analyzing, and graphically representing empirical information. They are sometimes called information graphics, or even just charts and graphs.The goal of visualizing data is to tell the story in the data.Telling the story is predicated …
ETL ETL is the set of processes by which data is extracted from various sources transformed and loaded into target systems. ETL stands for Extract, Transform and Load. Importance of ETL ETL technology is an important component of a complete enterprise data integration solution and …
SAP Business Objects Universe | Semantic Layer vs universe Semantic layer The semantic layer is an abstraction layer between the database and the business user that frees the business users from needing to know the data structures and technical names. It enables business users to …
Pentaho Data Integration Pentaho Data Integration (PDI) is an extract, transform, and load (ETL) solution that uses an innovative metadata-driven approach. It includes the DI Server, a design tool, three utilities, and several plugins. Pentaho tool is most frequently used in data warehouses environments. PDI …
What is R ? R is a free software programming language and software environment for statistical computing and graphics. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. What r can do ? Using R Programming …
Data Preprocessing Data Preprocessing or Dataset preprocessing is a activity which is done to improve the quality of data and to modify data so that it can be better fit for specific data mining technique. Also Read : What is Data Management? Benefits of Data …
Data Mining Issues/Challenges Data Mining Issues : Major Issues and challenges one can face with Data Mining Process are Mining Methodology User Interaction Efficiency and Scalability Diversity of Database Types Society Data Mining Issues/Challenges – Mining Methodology Mining Methodology involves the investigation of new …
Data Mining Data mining (knowledge discovery from data).Extraction of interesting (non-trivial, implicit, previously unknown and potentially useful) patterns or knowledge from huge amount of data. Alternative names of data mining : Knowledge discovery (mining) in databases (KDD), knowledge extraction, data/pattern analysis, data archeology, data …