Forensic Data Analysis 
and Services

Step 1: Developing Procedure and Policies

Cybersecurity specialists understand how valuable the data is and are aware that it can be compromised if it isn’t handled appropriately. Thus, it's crucial to create protocols that can specify how to set up mechanisms for retrieving evidence, where to store the retrieved evidence and when to authorize forensic investigators to recover prospective evidence, and how to document the operations.

Step 2: Assessing the Evidences

In the second phase, an evaluation of potential evidence of cybercrime is performed. This data forensics or forensic analysis evaluation comprises categorizing the relevant cybercrime such as one related to social engineering, phishing, identity theft, etc. Before entering data as evidence, the investigator must determine the integrity and origin of data.

Step 3: Acquiring the Evidences

This phase entails creating a thorough, methodical approach to gathering evidence. All the information must be recorded, preserved, and documented before, during, and after the evidence acquisition. Forensic data analysis becomes futile in the absence of evidence, therefore effective policies maintaining the integrity of potential evidence should be applied in this step.

Step 5: Documenting and Reporting

Here, forensic analysis or data forensics investigators retain a record of all techniques used during the investigation including methods to verify system's functionalities as well as copying, retrieving, and storing data. Reporting and documentation demonstrate how user integrity was maintained and ensured that all other parties comply.

Step 4: Examining the Evidences

There are certain processes for retrieving, copying, and storing evidence in an appropriate database to examine potential evidence. It encompasses a variety of tactics and techniques for analyzing information such as retrieving recently deleted files/media or employing analysis tools to search for data archives with particular file types.

Detailed, domain-specific assessment, consulting, and support to integrate cutting-edge analytical processes with data modelling and designing.

Data Archival as per industry regulations for automated, efficient data profiling and data cleansing.

Streamline data collection, processing, and analysis from multiple sources and IT ecosystems to ensure a universal data architecture.

Utilize Big Data solutions to identify resource and cost-hungry processes, approaches, systems. Fix inefficiencies and improve productivity to reduce overall enterprise expenses.

Monitor and manage infrastructure health in real-time to prevent sudden outages and disasters

Gain universal visibility to business functions, systems, processes, workflows, applications, and performances in real-time, via intuitive analytical dashboards and smart reporting.

End-to-end data ingestion and management across all cloud landscapes. Deploy cloud-native data analysis and advanced automation to optimize critical business processes and outcomes.

Defined data engineering, data modernization, data ops project management and tool integrations with flexible choices of ETL tools and services

Seamless AI and data governance - compliance with local, national regulations and industry standards, up to date methodologies

Seamlessly address all infrastructure-networks and platform to deploy advanced forensic data analysis services. Embrace ready-made models and libraries to deploy AI on-prem, across remote ecosystems, and edge environments.