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DataScape Analytics Solution

Data Stored in One Location, Made Actionable and Scalable

Government organizations rely on many systems and applications to generate and store data critical to delivering their missions. But many face a common challenge. The value of these systems is often unachievable because the data they produce is inaccessible by other systems across the enterprise.

An enterprise data lake can solve this challenge. Data lakes hold, process, and analyze massive amounts of data, regardless of the format or purpose of the source data. MCP’s DataScape™ analytics solution brings native data from multiple sources into a data lake in real-time. It provides a comprehensive platform of tools for users to interact with the data easily.

DataScape: An Artificial Intelligence and Machine-Learning Platform

Implementing MCP’s DataScape analytics solution enables organizations to have:

  • Significantly improved value derived from data
  • Machine learning and artificial intelligence combined with an enterprise data lake
  • Analytics targeted to enhance decision-making that fosters a data-driven culture
  • New analytics capabilities not previously possible
  • Boosted productivity among staff
  • The ability to store data without overly structured design and without requiring knowing how it should be used
  • A new approach to data migration that eliminates the need to transform and load partial and inaccurate historical data
  • New abilities to generate data analyses and reports



Use Cases

911 call performance trends, visualizations, and metrics to improve time to dispatch

Viewing of court case volumes, trends, and sentencing across jurisdictions

Predictive call and dispatch analytics to predict 911 call volumes and response requirements

Matching of fingerprint arrest records to court case dispositions to improve criminal history match rates

Analytics and Visualizations 

Data dashboards and visualizations ensure users can access data in an interactive, singular platform. Users can move structured and unstructured data from various sources into the solution. They then can be stored, processed, and analyzed.



  • Large-scale, simplified data linking between disparate sources
  • A configurable user interface that empowers managers to “slice” data to see trends and report to executives and funders
  • Agencies contribute only the data they authorize, giving each data provider control over policy compliance and access by other users
  • The ability to stream new data into a shared source in near-real-time, as individuals create new records in their systems of record

Machine Learning and Artificial Intelligence

Organizations that want to go deeper with data management can apply machine learning and artificial intelligence. These tools identify patterns and anomalies, form conclusions, present analysts with probable results, and help decision-makers “connect the dots” based on newly aggregated and contextualized data.


  • Statistical algorithms are “trained” to reveal statistical clustering of similar data.
  • Analysts can fine-tune Algorithms to balance pattern-matching with the added noise that false-positive matches introduce.
  • Data from multiple sources can help verify identity and provide a complete record, for example, matching individuals with identifiers, last known addresses, and involvement across various systems.
  • Machine learning performs probabilistic matching on a massive scale. Agencies can see patterns they would never be able to uncover using traditional tools. The insights gained can drive efficiency and better manage workloads in the face of staff shortages.
Big Data is Helping Just Organizations Address Their Biggest Challenges

Trends: Big Data is Helping Just Organizations Address Their Biggest Challenges

The courts can benefit tremendously from recent advances in big data tools. This article explores some artificial intelligence (AI) and machine learning (ML) tools expected to grow in the justice sector:

  • AI/ML-Assisted Document Entry and Processing
  •  Chatbot and Virtual Assistants
  • AI/ML-Assisted Data Quality Tools
  • AI/ML-Assisted Judicial Decision-Making
Data-Driven Criminal Justice

Podcast: Data-Driven Criminal Justice

This podcast episode explores how data integration can improve the criminal justice process and result in better information and more effective and data-driven decision-making.


An Introduction to Data Lakes for Public Safety and Justice Organizations

Explore the concept of data lakes and how DataScape combines a data lake with machine learning and artificial intelligence to integrate data from a variety of systems, such as

  • Records-Management System
  • Computer-Aided Dispatch Incident Data
  • DNA Database Indexes
  • External Databases, e.g. evidence and incident reports

Let’s Talk

How can we support your mission? From design and procurement to building and management, our national team of experts is here to help…because the mission matters.


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