Big Data Compliance, Security and Governance Solutions

How to Building Secure Big Data Platform?

• A unified, secure Big Data platform performs Data Integration and Migration of the data.
• Execute, create and maintain different scripts to integrate and migrate the data from various sources to Hive.
• Secure Mode Apache Hadoop, Apache Spark operations and authenticated team members access clusters with different access level and permissions.
• Optimization of analytical queries performed on Hive using Apache Spark.
• Infrastructure Automation of Apache Hadoop and Apache Spark Cluster.

What are the major security challenges in Big Data?

The below highlighted are the challenges for Big Data Security

Infrastructure Security

• Secure Distributed Processing of Data
• Security Best Actions for Non-Relational Databases

Data Privacy

• Data Analysis through Data Mining Preserving Data Privacy
• Cryptographic Solutions for Data Security
• Granular Access Control

Data Management and Integrity

• Secure Data Storage and Transaction Logs
• Granular Audits
• Data Provenance

Reactive Security

• End-to-End Filtering & Validation
• Supervising the Security Level in Real-Time

Data Management

• Data Access Control
• Data Quality 

XenonStack's Big Data Security Solution Offerings 

• Unified Big Data platform to integrate different sources and Data Migration tasks using a single dashboard.
• Enable security for the Apache Hadoop and Apache Spark clusters with auto deployment process and optimal query execution time of analytical queries and Machine Learning algorithms.
• Infrastructure Automation using Ansible
• Enable Security using Apache Knox and Apache Ranger
• Create Playbooks For Auto-Deployment
• Enable Security and User Authentication using Apache Kerberos
• Data Migration To MySQL and Apache Hadoop Cluster
• Optimization of Spark Execution Engine
• Enable Monitoring and Performance Metrics Visualization in Graphene

Big Data Platform with Apache Hadoop Security Architecture

Authentication and Access Control are key components involved in securing Apache Hadoop. Various indispensable solutions to protect from threats should have -

• Kerberos Authentication
• Real-Time Alerting
• Authorization Policies
• Delegation Tokens
• System Directory Protection
• Secure Data Node
• Network Encryption and Security
• HDFS Authentication
• Logging Transactions and Activities
• File Encryption
• Minimize Resource Utilisation
• Hadoop Agnostic
• Data Encryption

Why choose Apache Hadoop?

• Continuity and Stability
• Unified Authentication and Authorisation
• Data Protection
• Fault-Tolerant
• Cost Effective Storage Solutions
• Scale-Out Architecture
• Confidentiality and Integrity
• Real-Time Applications of Secured Apache Hadoop
• Telecommunications for network expansions
• HealthCare to prevent diseases through Predictive Maintenance
• Compatable with Internet of Things (IoT ) Devices
• Retail to analyze data and satisfy customer needs
• Asset Management in the Manufacturing Industry for producing energy
• Interactive Analysis
• Data Streaming