Data Intelligence Consulting Services

Understanding your Current Business Intelligence Posture for Rapid Growth and Performance

Visual analytics with a performant data architecture as a cohesive platform serves as a focal point for many organization's business intelligence strategy. It helps communicate performance-based goals to decision makers, individual contributors, and partners. As your reporting initiative expands, you may have questions about best practices for scaling, security, sharing, deployment, and management. We're here to help you navigate these areas and ensure your PowerBI strategy is successful

Start a conversation with us and our knowledgeable experts to:

• Gain insights with tailored recommendations on best practices for data quality, data modeling, and calculating essential metrics.
• Receive guidance on envisioning your business intelligence initiative to encourage adoption and drive positive change.
• Explore key concepts in creating compelling business intelligence and data analytics reporting as part of your market offerings.
• Delve into the challenges and opportunities of securing, scaling, and nurturing a robust PowerBI ecosystem for your business.

Customer Background

A local government agency responsible for maintaining law and order, ensuring public safety, and preventing criminal activities. With increasing crime rates and limited resources, DPS aims to leverage data analytics to optimize resource allocation, enhance crime prevention strategies, and improve overall community well-being.

Objective

The primary goal of this data analytics project is to develop a predictive policing model that assists law enforcement agencies in identifying high-risk areas, allocating patrols efficiently, and preventing crimes before they occur.

Approach

• Data Collection and Integration
• Exploratory Data Analysis (EDA)
• Feature Engineering
• Predictive Modeling
• Evaluation and Feedback Loop

Outcomes

• Reduced response times: Officers arrive faster at crime scenes.
• Targeted resource allocation: Patrols focus on high-risk areas.
• Crime prevention: Proactive measures lead to fewer incidents.
• Enhanced community trust: Transparent and data-driven policing.

Customer Background

A project for a financial services leading investment firm specializing in wealth management, asset allocation, and portfolio optimization. With a diverse client base and a vast array of financial products, the company aims to enhance decision-making, improve risk management, and maximize returns for its investors

Challenges

• Data Complexity: Managing data from various sources (market data feeds, client transactions, economic indicators) was becoming increasingly complex.
• Manual Reporting: Generating reports for portfolio performance, risk exposure, and compliance was time-consuming and error-prone.
• Market Volatility: Rapid market changes required real-time insights to adjust investment strategies promptly.

Outcomes

• Enhanced Decision-Making: Portfolio managers made informed investment decisions based on real-time data.
• Risk Mitigation: Early detection of market anomalies and risk exposure helped prevent losses.
• Client Satisfaction: Customized reports and transparency improved client trust.
• Competitive Edge: The company gained a competitive advantage by leveraging data-driven insights.

Compare Critical Financial Business Intelligence Metrics Across Organizational Units

Compare P&L and Balance Sheet metrics across companies, organizations, franchisees, departments, associations or any group of entities across a similar set of financial metrics for cooperative iterative performance improvement.

When companies pool their data it provides visibility into market metrics relative to a much larger organization. By comparing performance, individual organizations can understand best practices and performance opportunities for the group.

Features of the Group Financial template include:

• Common P&L metrics for sales, costs, expenses, gross & net profit
• Balance sheet metrics for receivables, payables, net worth, current & debt ratio
• Comparison of metrics by YTD, month, previous periods
• Selectively compare and drill down metrics for sales, expenses, costs, assets, liabilities, net worth, F&I
• Compare individual entities to average, variances from previous periods, performance thresholds

Easily integrate custom accounting codes, industry, demographics or other external data for even more visibility into process improvement and actionable insights.