Big Data Testing Consulting, Services and Solutions Company
Automated Big Data Testing Solutions for any Volume, Variety, and Velocity of Data.
Solutions
Big Data Testing Services and Strategy
XenonStack, being automated Big Data Testing Solution Company helps you check organized and unstructured informational indexes, patterns, approaches and innate procedures living at various layers in your big data platforms, for example, ‘Apache Sqoop’, ‘Apache Nifi’ at Data Ingestion Layer, ‘Spark’, ‘MapReduce’, ‘Apache Pig’ at Data Processing Layer and ‘HBase’, ‘Hive’, ‘Cassandra’ at Data Storage Layer. Our Continuous Performance Testing Services
This Architecture helps in designing the Data Pipeline with the various requirements of either Batch Processing System or Stream Processing System
Big Data Migration Testing
Data Migration Test Strategy
Source to Target (NoSQL DB/Hive/HDFS) Field Validation
Data Accuracy Validation Post Migration
Multi-Source Data Integration Validation
Security Testing
Security Test Assessment
Role Based Security Testing
Default Permission Configuration Check
Data Node and Name Node direct access validation
Performance Testing
Performance Test Strategy
Performance Monitoring Scripts Creation
Performance Monitoring and Identifying Bottlenecks
Big Data Sources Extraction Testing
Data Processing/ETL Test Strategy
Data Extraction Validation
MapReduce Jobs Validation
Spark Jobs Validation
Hive Queries/Pig Jobs Validation
Data Storage in Hadoop Distribution File
System (HDFS) and NoSQL Database
DB Validation
Big Data Ecosystem Testing
Referential Integrity Tests
Constraints Check
Metadata Analysis
Statistical Analysis
Data Duplication Check
Data Accuracy/Consistency Check
Data Analytics and Visualization Testing
Report Objects Validation
Reports Validation
Dashboards Validation
Mobile Reports Validation
Visualization Validation
Testing Methods and Tools for Pre-Hadoop Processing
Big Data systems typically processes a mix of structured data, unstructured data, and semi-structured data. Data sources can include a local file system, HDFS, Hive Tables, Streaming Sources, and Relational or other databases.
Typical Testing Methods
Data Type Validation, Range and Constraint Validation, Code and Cross-Reference Validation, Count of Rows Validation in ETL Data Process, Structured Validation
Testing Methods and Tools for Hadoop MapReduce Processes
Hadoop MapReduce is a software framework for easily writing applications that processes vast amounts of data in-parallel or large clusters.
Methods and Testing Tools for Hadoop MapReduce Processes
MRUnit - Unit Testing for MR Jobs, Local Job Runner Testing - Running MR Jobs on a single machine in a single JVM, Pseudo-Distributed Testing - Running MR Jobs on a single machine using Hadoop, Full Integration Testing - Running MR Jobs on a QA Cluster
Testing Methods and Tools for Data Extract and EDW Loading
Data Warehouses play a vital role in Big Data. Companies rely on Data Warehouses for collecting information on their business operations, markets, and client behavior to identify patterns, and collect the results to identify more business opportunities and operational improvements.
Typical Testing Methods -
The data in the data sources is validated directly in the Data Warehouse, The data is validated from the data sources through each step of the extract, including the final load in the Data Warehouse
Testing Tools for Data Extract and EDW Loading
SQL Server Integration Services (SSIS), Informatica PowerCenter, OpenText Integration Centre, Cognos Data Manager
Testing Methods and Tools for Big Data Analytics
Big Data Analytics refers to the process of collecting, organizing, and analyzing large sets of data to discover patterns and reporting useful information. Specific areas within analytics include Predictive Analytics, Enterprise Decision Management, Retail Analytics, Predictive Science, Credit Risk Analysis, and Fraud Analytics.
Testing Methods for Big Data Analytics
Validating the Dashboard Report Model, Checking the Source Record Count and Target Record Count, Authentication Testing, Data Level Security, Bursting the Reports, Buzz Matrix Validation, User Acceptance Criteria, Time Series Functions Validations, End-to-End Testing
Tools for Big Data Analytics
Apache Falcon - Falcon simplifies the development and management of data processing pipelines with a higher level of abstraction taking the complex coding out of data processing applications by providing out-of-the-box data management services.
Testing Methods and Tools for Performance Testing and Failover Testing
Identify response time, maximum online user data capacity size, and maximum processing capacity with Performance Testing. Failover Testing validates the recovery process and ensures data processing continues correctly when switched to other data nodes.
Testing Techniques for Performance and Failover Testing
Static/Default Installation, Backup/Restore, Data Replication, Rolling Installation
Testing Tools for Performance Testing and Failover Testing
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