- Big Data Analytics - Data Scientist
- Big Data Analytics - Data Analyst
- Key Stakeholders
- Core Deliverables
- Big Data Analytics - Methodology
- Big Data Analytics - Data Life Cycle
- Big Data Analytics - Overview
- Big Data Analytics - Home
Big Data Analytics Project
- Data Visualization
- Big Data Analytics - Data Exploration
- Big Data Analytics - Summarizing
- Big Data Analytics - Cleansing data
- Big Data Analytics - Data Collection
- Data Analytics - Problem Definition
Big Data Analytics Methods
- Data Analytics - Statistical Methods
- Big Data Analytics - Data Tools
- Big Data Analytics - Charts & Graphs
- Data Analytics - Introduction to SQL
- Big Data Analytics - Introduction to R
Advanced Methods
- Big Data Analytics - Online Learning
- Big Data Analytics - Text Analytics
- Big Data Analytics - Time Series
- Logistic Regression
- Big Data Analytics - Decision Trees
- Association Rules
- K-Means Clustering
- Naive Bayes Classifier
- Machine Learning for Data Analysis
Big Data Analytics Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Big Data Analytics - Core Depverables
As mentioned in the big data pfe cycle, the data products that result from developing a big data product are in most of the cases some of the following −
Machine learning implementation − This could be a classification algorithm, a regression model or a segmentation model.
Recommender system − The objective is to develop a system that recommends choices based on user behavior. Netfpx is the characteristic example of this data product, where based on the ratings of users, other movies are recommended.
Dashboard − Business normally needs tools to visuapze aggregated data. A dashboard is a graphical mechanism to make this data accessible.
Ad-Hoc analysis − Normally business areas have questions, hypotheses or myths that can be answered doing ad-hoc analysis with data.