ETL and ELT for Data Pipelines and Management

Understanding Data Migration Techniques and Best Practices

Data Migration involves extraction, transformation, and loading. Comprising the following steps

Transferring data
Modification of Workflows and processes
Integration with existing solutions
Implementation into the new system

The primary flow of data migration involves

Extraction
Transformation
Cleansing
Validation
Loading

Challenge for Data Migration and Application Performance

Application Performance Issues while migrating massive amounts of data during Data Migration.
Lack of visualization of Data Migration in Real-Time to monitor the load and throughput of Data Pipeline.
No mechanism to validate migrated data to Hadoop on a daily basis.
Secure remote access to Data Migration Tool.

Solution Offered to Build Data Migration Platform

Develop a Data Migration platform and analyze Hive queries with the latest technologies and distributed Agile Development methods.
Build A Data Migration Platform To Migrate Data From Oracle To Hive.
Increase Hive Query Performance.

Predictive Analysis Applications in Retail

Predictive Analysis along with Retail have leveraged the power of Big Data by providing improved customer service, targeted promotions, Decision Making, and Supply Chain Analytics.

Real-Time Applications of Predictive Analysis in Retail involve

Customer Behaviour Analytics
ClickStream Analytics
Predictive Maintenance
Fraud Detection and Prevention
Inventory Management
Asset Management
Recommendation Engine
Forecasting Trends

Increase in Risk management, Precise Marketing and Loss prevention in predictive analysis with Retail has led to improved marketing and customer engagement, price optimization, data-driven insights with the best use of statistical algorithms, data mining, and Machine learning techniques.