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Magic EdTech uses the following processes to determine whether your data can answer the questions that you want answered.
Data Engineering
Capturing Data
- Data capturing & storage
- Metrics
- Research
Processing
- Pattern identification
- Understand usage trends
- Data optimization
Deriving Insights
- Real-time insights
- Data-driven decision making
- Performance analytics
- Content usage analytics
Technologies
Data Visualization
- Tableau
- Qlik
- HTML5
- Data-driven documents
Data Processing Tools
- Hadoop
- Spark
- HDInsight
- Amazon EMR
- Cascading
Data Storage Infrastructure
- Cloudera
- mongoDB
- Couchbase
- SQL Azure
Data Analytics as a Service
- High data proliferation due to Mobilee, IoT, and internet growth
- Unstructured data to result-oriented interpretation
- Faster and accurate decision making
- Developing new and curated content
Content Usage Analytics
Learning Analytics
Student Progress Flow
Assessment Analytics
Helping publishers and EdTech organizations in transforming learners’ experience through analytics-driven solutions. Digital learning offers opportunities for capturing data directly related to a student’s interaction with the learning systems. Magic EdTech develops systems to analyze this data by capturing it and generating meaningful inferences focused on learning outcomes.
