analytics, data analysis, data, business intelligence, data analyst, business analytics, big data, analysis, data management, data mining, cloud computing

Data Analytics Certifications

Why ?

Data Analytics is one of the most important new fields today. It is used in marketing, services, finance, healthcare, cyber security, aviation, education and almost every other field. In H.R., application of analytics helps companies manage human resources for hiring, promoting, assigning responsibilities, and similar human resource problems. A common application of business analytics is portfolio analysis. In this, a bank or lending agency has a collection of accounts of varying value and risk.

Digital analytics is a set of business and technical activities that define, create, collect, verify or transform digital data into reporting, research, analyses, recommendations, optimizations, predictions, and automations. This also includes the SEO (Search Engine Optimization) where the keyword search is tracked and that data is used for marketing purposes. Security analytics refers to information technology (IT) to gather and analyse security events to understand and analyse events that pose the greatest risk.

Deeper Specializations

Duration: 24 Hours
Prerequisites: Nil
Tools: MS Excel, Sql server Express Edition
What is Business Intelligence and Data Warehouse?
BI Life Cycle
Business Game
Introduction to Database
Concept of Entity and Entity Relationship
ER Practice
Data Modelling Fundamentals
Data Modelling Practice
Excel Exercise – Reports and Dashboards
Introduction to ETL Tools
Introduction to Reporting Tools

Duration: 64 Hours
Prerequisites: Awareness Course
Licensed Tools: MSBI, Informatica + Tableau
OpenSource Tools: Pentaho
Revision
ETL
Tool Architecture
Basic Transformations
Advanced Transformations
Assignment
Reporting
Tool Architecture
Basic Visualization
Filtering
Aggregation
Drill Down
Drill Through
Dashboarding
Assignment
Duration: 120 Hours
Prerequisites: Proficiency Course, Java Programming
Licensed Tools:
OpenSource Tools: Hadoop, R
Awareness Revision
Fundamentals of Big Data
Hadoop and Hadoop Framework (HDFS, YARN, MapReduce)
MapReduce Programming
Introduction to Statistics
Probability and Probability Distributions
R Programming
Statistical Inference
Estimation Theory
Testing of Hypothesis
Regression Analysis
Time Series Analysis
Data Mining Techniques
Supervised Learning
Unsupervised Learning

Duration: 120 Hours
Prerequisites: Proficiency Course
Licensed Tools: MSBI, Informatica + Tableau
OpenSource Tools: Pentaho
Awareness Revision
ETL Tool Revision
Reporting Tool Revision
Understanding Project Requirements
Data Model Development
Target to Source Mapping Document
ETL Development
Report Development