Data Analytics

For any fairly large-sized enterprise, machine data is perhaps the richest and largest source of data which can be harvested to gain critical, real-time business insights and knowledge. This can then be used to make mission-critical business and policy decisions. The general approach to data analytics can be summed up as:

  • Collect/structure/index data
  • Generate alerts and action points
  • Enrich data based on experience from actions
  • Report and visualise insights
  • Analyse and predict (based on current data and previous insights)

Applying the above approach to data analytics gives birth to a new class of business analytics, which can then be applied to use cases/business areas.

Business Process Analytics

Business process analytics provides end-to-end, real-time insights across the various business process, enabling management to make relevant decisions based on latest knowledge, identify process bottlenecks, perform root-cause analysis of identified issues etc.

Customer Experience Analytics

This involves measurement and analysis of customer behavior and identifying opportunities to increase customer engagement and satisfaction. This also helps in revenue optimisation by increasing conversions (cart-to-checkout).

Product Analytics

This provides analysis of product feature adoption, usage and effectiveness, resulting in better user engagement. The biggest application of this is to identify most used/unused features and refine product feature offerings.

Digital Marketing

This provides real-time insights into marketing campaigns, and user engagement thereof across multiple channels. This helps to evaluate the effectiveness of marketing campaigns and customer segmentation, thereby enabling more focussed campaigns.

SIEM (Security Information and Event Management)

SIEM is a critical component of managing security of enterprise data and analysing threat and event data to mitigate risks and protect against future threats. The primary benefits of an effective SIEM solution include:

  • Comprehensive security analytics from a wide array of data sources
  • Streamlining advanced threat investigations
  • Rapid incident analysis with fast answers and proactive threat hunting
  • Machine learning-based advanced analytics for rapid anomaly and threat detection
  • Mitigation of insider and external threats
  • Improvement in operational efficiency with automated and manual decisions

The business use cases of SIEM solutions in enterprises are:

  • User Behaviour Analytics
  • Insider Threat Detection
  • Advanced Threat Detection
  • Fraud Detection and investigation
  • Compliance Reporting
  • Rapid Incident Investigations
  • Event Log Management

Solution implemented using: