Narwal
  • Let's Talk
  • Home
  • About us
  • Services
    • AI
      • ML
      • Generative AI
      • Intelligent Automation
    • Quality Engineering
      • Test Advisory & Transformation Services
      • Quality Assurance
      • Software Test Automation
      • Enterprise Apps Testing
    • Data
      • Data Engineering
      • Data Modernization
      • Data Monetization
    • Cloud
      • Cloud Migration
      • Cloud Modernization
      • Data Management
  • Careers
  • Insights
CONTACT US
  • Data Use Cases
  • Dec 08

Customize Business Intelligence Platforms

Customize Business Intelligence Platforms
Operational Excellence: Optimize enterprisewide processes and operations 

System: Business Intelligence Platform, Data Matching Process, Workload Management Tool

Actor: End Users, Data Analysts, Fraud Analysts, Project Managers

Scenario:

End users in an organization want to customize their business intelligence platforms to discover relevant data more efficiently and reduce user effort.

End users have access to a variety of data sources and want to customize their dashboards and reports to display the most relevant and actionable information for their specific needs.

They utilize the customization features of the business intelligence platform to personalize their data views, configure alerts for important metrics, and automate data refreshes.

By customizing the business intelligence platform, end users can optimize their data discovery process, minimize manual efforts, and focus on analyzing insights for informed decision-making.

Use Case

Use Case Name: Customize Business Intelligence Platforms for End Users to Discover Relevant Data and Reduce User Effort

Primary Actor: End Users

Goal: To customize business intelligence platforms to discover relevant data more efficiently and reduce user effort.

Pre-conditions: End users have access to a business intelligence platform with customization capabilities.

Post-conditions: End users have personalized data views, configured alerts, and automated data refreshes to enhance their data discovery process and reduce manual efforts.

Operational Excellence: Optimize enterprisewide processes and operations 

System: Business Intelligence Platform, Data Matching Process, Workload Management Tool

Actor: End Users, Data Analysts, Fraud Analysts, Project Managers

Scenario:

Data analysts and fraud analysts in an organization want to replace manual data-matching processes with algorithms that detect anomalies and fraud.

The current manual data-matching processes are time-consuming and prone to errors, limiting the efficiency and effectiveness of fraud detection.

Data analysts and fraud analysts work together to develop and implement algorithms that can automatically identify anomalies and potential fraud patterns based on predefined rules and statistical models.

By deploying automated data-matching algorithms, the organization can improve the accuracy and speed of fraud detection, enabling timely mitigation of risks.

Use Case

Use Case Name: Replace Manual Data-Matching Processes Using Algorithms that Detect Anomalies and Fraud

Primary Actor: Data Analysts, Fraud Analysts

Goal: To replace manual data-matching processes with algorithms that detect anomalies and fraud.

Pre-conditions: Manual data-matching processes for fraud detection are in place.

Post-conditions: Automated data-matching algorithms are deployed, improving the accuracy and speed of fraud detection processes.

Operational Excellence: Optimize enterprisewide processes and operations 

System: Business Intelligence Platform, Data Matching Process, Workload Management Tool

Actor: End Users, Data Analysts, Fraud Analysts, Project Managers

Scenario:

Project managers in an organization want to deploy an automated workload management tool to improve task allocation and project management.

The current task allocation and project management processes are manual and decentralized, leading to inefficiencies and coordination challenges.

Project managers research and select a suitable workload management tool that can automate task allocation, facilitate resource management, and enable better collaboration among team members.

By deploying the automated workload management tool, project managers can streamline task allocation, optimize resource utilization, and improve overall project management efficiency.

Use Case

Use Case Name: Deploy an Automated Workload Management Tool to Improve Task Allocation and Project Management

Primary Actor: Project Managers

Goal: To deploy an automated workload management tool to improve task allocation and project management.

Pre-conditions: Manual and decentralized task allocation and project management processes are in place.

Post-conditions: An automated workload management tool is deployed, enhancing task allocation, resource management, and overall project management efficiency.

Related Posts

The Rise of Edge Computing: Unlocking Innovation Through Data Accessibility
Blog Data

The Rise of Edge Computing: Unlocking Innovation Through Data Accessibility

Edge computing delivers storage, computing, and network capabilities to the local points of a network, promoting reduced latency, lower costs, and better performance. According to MarketsandMarkets, the global edge computing market is projected to be…

khitish@
  • Jan 18
The Future of AI: Why 75% of Organizations are Moving Towards Operationalizing AI
Blog Data

The Future of AI: Why 75% of Organizations are Moving Towards Operationalizing AI

The world of artificial intelligence (AI) has changed rapidly in recent years. In 2020, Gartner identified the top 10 data and analytics technologies, with AI topping the list [1%5E]. According to Forrester, 12% of companies…

khitish@
  • Dec 15

Post a Comment

Categories

  • Blog
  • Use Cases
  • Success Story

Latest Post

Driving Change with Generative AI and Hyperautomation

Driving Change with Generative AI and Hyperautomation

  • February 28, 2024
The Rise of Conversational AI and Chatbots

The Rise of Conversational AI and Chatbots

  • February 23, 2024
Hyperautomation The Future of Business Automation

Hyperautomation The Future of Business Automation

  • February 19, 2024
The Rise of Cloud Computing

The Rise of Cloud Computing

  • February 14, 2024

“We’re an AI, Quality Engineering, Data and Cloud company”

  • contact@narwalinc.com
Linkedin Twitter Facebook Youtube

Quick Links

  • Home
  • About us
  • Our Services
  • Career
  • Insights
  • Contact

Services

  • AI
  • Quality Engineering
  • Data
  • Cloud

Headquarters

8845 Governors Hill Dr, Suite 201

Cincinnati, OH 45249

Other Offices

Cincinnati | Jacksonville | Indianapolis | London | Hyderabad | Bangalore | Pune

Narwal | © 2024 All rights reserved

  • Privacy Policy
  • Terms & Conditions

AI/ML

  • ML
  • Generative AI
  • Intelligent Automation

Automation

  • Transformation Services
  • Intelligent Automation
  • Technology Assurance
  • Business Assurance

Data

  • Data Engineering and Management
  • Data Science
  • Reporting and Analytics

Cloud

  • Cloud Migration
  • Cloud Modernization
  • Cloud Management