The incredible eruption in the IT urge, data volumes, velocities and varieties have created intensified concerns over how to guarantee quality across the big data & data analytics ecosystem.
A meticulous testing approach is essential to offer impeccable quality in big data & data analytics testing. Indium will intensify your testing speediness, improve your testing exposure (up to 100%), and increase the level of excellence within your Big Data store.
With the increasing challenge of storage, processing, and accessing the data, Indium understands that Big Data testing is hard to do without the right tools and technologies.
Indium software offers a broad spectrum of big data analytics testing services including,
Big Data sources Extraction Testing
Data Migration Testing
Data Quality in Big data
Security and Performance testing
Big data Ecosystem Testing
Since Bigdata testing deals with huge amounts of data, which is mostly in terabytes, we use the following strategies in data validations.
Batch Data Processing Test
This test involves testing processes in which the data is run when the application is in batch processing mode. Batch processing storage units such as HDFS are used to process the application.
Real-Time Data Processing Test
In this type of testing, we work with data when it is in real-time processing mode and test the resultant process rules. Real-time processing tools like Spark are used to run the application.
Interactive Data Processing Test
In this type of testing, we simulate a real-life user by integrating real-life test protocols that interact with the app. Tools like HiveSQL are the processing tools used in the interactive data processing mode.
Big Data Testing stages
Our general approach to test a Big Data Application involves the following stages.
Data Ingestion Testing
Our data Ingestion testing practice involves importing, transferring, loading and processing of data to store in the database. The input data source varies from CSV, Sensor logs, social media etc.
Data Processing Testing
Our focus in this stage is on aggregated data. We validate the business logic of the ingested data for correctness. It is further validated by comparing the input files with the output files.
Data Storage Testing
We verify whether the output data is precisely loaded into the warehouse by evaluating the warehouse data with output data.
Since Big data involves processing of significant amount of data in a short span of time, Performance testing is recommended to avoid bottlenecks.
- Data Loading and Throughput – It is important to monitor the speed at which the data created in the data store and data consumed from various sources.
- Data Processing Speed
Sub-System Performance – The individual components of the overall application is tested here to identify possible bottlenecks
Functional Testing / Integration Testing
The complete front end of the application will be tested from data visualization to data ingestion. We test the front end of the application according to the user requirements.
Data Quality Testing
The output is usually stored in HDFS or any other warehouse. We compare the output data with the data in the warehouse and ensure that the data was loaded correctly in the warehouse.
Data Migration Testing
We can migrate data from an old system to a new system and ensure that there is no downtime and zero data loss with our data migration testing.
Business logic Validation Testing
We ensure that the business logic is implemented correctly when the ingested data is processed. We further validate this via comparison of the output and input files.
Indium Software Can
- Automate the Testing, Comparison and Reporting Effort
- Test Across Different Platforms
- Speed up Testing
- Be Launched by a Process, Run unattended & Auto-Email the Entire Team with Results
- Compare 100% of the data in your Big Data Implementation
Guaranteed data quality with Indium.
It confirms that the data you remove from sources remains intact in your target by investigating and quickly identifying any differences in your data at every touch point.
Indium Software’s Big Data & data analytics Testing Solution
Data Integration Testing
- Source System Extraction Completeness & Correctness
- Data Quality (Both Business and Technical) Completeness and Correctness
- Transformations Completeness & Correctness
- Subject Area Load Completeness & Correctness
Analytic Layer Testing
- Correctness: Each Analytic Report/Adhoc Environments should be Tested
- Look and Feel of the information
- Drill-Path Verification
- Regression Testing requires particular focus on Enhancement and Maintenance Efforts.
Data Repository Testing
- Subject Area Load Completeness and Correctness
- Referential Integrity
Indium provides solutions for Big Data application problems with their state of the art QA practices before the application is certified.
Along with big data testing, Indium’s testing solution for Big Data strategy covers data security, test data preservation and IT amenability as well. Indium is a vendor that not just understands your business, but can also use its expertise to comfort your digital conversion and to adapt to the shift from outdated methods to alternative, agile methods.
Our customers benefit from our approach as a result of
- Reduced cost and time
- Integrated expertise and positioning of test environments to offer test data
- Data security and amenability with data protection guidelines