Big Data Analytics Solution Development
Impala Intech implemented a big data analytics solution for a popular logistics company
Client’s Goal - Increased Big Data Efficiency
The client for the project was a leading market research company based in the US. They required a solution that could increase efficiency for big data analysis in the marketing & advertisement industry.
The Challenge for Impala
Business Challenges
The client wanted a system that could
- Cope with the continuously growing amount of data
- Analyze large amounts of data faster
- Prove to be future-proof
Technical Challenges
- Creating a system infrastructure that can handle large data structures
- Enabling comprehensive advertising channel analysis
- Migrating all their procedures from an old system to a new one
How Impala Intech Made it Possible
Parallel Operations
We ensured that both the old and new system were operating in parallel as per the client’s request
Data Preparation
It takes data from multiple sources like tv views, mobile device browsing history, etc. The module is capable of processing 1000 different types of raw data by transforming, parsing, merging or loading it into the systems
Data Warehouse
The system linked user ID’s from different data sources according to the mapping rules, and ETL for the entire block was written in Python
Desktop Application
The new system enabled a cross analysis of almost 30,000 attributes and built intersection matrices allowing multi-angled data analytics for different markets
Our Tech Stack
AWS
Microsoft Azure
Hadoop
Python
The Success of Our Solution
The client was able to analyze and gather insights from almost 30,000 attributes and expand the customer analysis process.
The updated system can now solve queries 100 times faster than the previous outdated system.
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