mission critical Analytics for Public Sector

Transform Data into
Actionable Intelligence

Transform Data into Actionable Intelligence
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Trusted by Leading Government Agencies

Trusted by Leading
Enterprises

public sector challenges

Slow Decision-Making 

Agencies struggle to turn vast data into actionable intelligence, delaying decisions and reducing operational effectiveness. 

Security and Compliance

Legacy systems expose sensitive data to increasing cyber threats, making it challenging to meet security standards and protect information. 

Escalating Costs

Outdated infrastructure increases costs and inefficiencies, diverting resources from critical missions and modernization efforts. 

Scalability Challenges 

Growing data volumes, the rise of edge and AI use case strain legacy systems, limiting agencies' ability to scale and adapt. 

public sector
challenges

yellowbrick’s strengths

Real-time Analytics

Migrate from outdated platforms with up to 100x performance improvements and real-time analytics, turning IoT and other data into actionable intelligence. 

Battle-tested Security

Maintain full control over data in the public cloud, including GovCloud, on-premises, edge, or hybrid multi-cloud, with Yellowbrick’s Private Data Cloud and IL4/5/6 and FIPS 140-2 compliant AES-256 encryption.

Cost Efficiency

Scale with predictable performance and costs, reduce data center footprints (if on-premises), and free up resources for mission-critical operations. 

Future-Proof

Hybrid multi-cloud design enables agencies with a flexible infrastructure that supports secure, integrated operations for new edge and AI use case.

yellowbrick’s
strengths

case study

How NAVSUP Modernized Petabyte-Scale Data Platforms with Yellowbrick 

Problem

NAVSUP faced challenges modernizing legacy data platforms as part of a broader cloud migration strategy. Existing infrastructure couldn’t efficiently process the growing volume of data, impacting decision-making and operational efficiency. 

Solution

Yellowbrick provided a unified data experience across cloud and on-premises environments, enabling faster data ingest, processing, and reporting in line with the DoD’s goals of integrating advanced analytics with cloud solutions to optimize operations. 

Results

NAVSUP reduced its data center footprint, lowered energy consumption, and streamlined data operations, positioning itself for future cloud expansion, aligning with the DoD’s emphasis on modernizing infrastructure while ensuring cost-efficiency and operational readiness. 

solution briefs

Load and Query
Concurrently

Run analytics and data engineering together without conflict or complex orchestration.

Streaming
Ingestion

Stream, ETL, and query in the same database. Avoid multiple solutions.             

Keep Data
Local

Have absolute confidence in where data is located and processed.                                  

Elastic
Scale

Handle unlimited concurrency, multi-tenancy, AI complexity or massive volumes.

solution briefs

trusted migration process

DEDICATED YELLOWBRICK CUSTOMER SUCCESS TEAM

STEP 1:
Information Transfer & Assessment 

Objective: Gather necessary information and evaluate the customer’s environment.
 
Action: Transfer details from the account team and validate workflow, architecture, and data sources (ETL, BI tools). 

Outcome: A complete understanding of the customer’s environment and migration components. 

STEP 2:
Build Migration Inventory 

Objective: Identify all components involved in the data migration process. 

Action: Compile an inventory of objects, views, schemas, stored procedures, tables, roles, UDFs, etc. 

Outcome: A comprehensive list of components required for migration. 

STEP 3:
Define Migration Path & Success Criteria

Objective: Establish the migration approach and define success metrics. 

Action: Choose between Lift & Shift, object mapping, or code refactoring, and agree on functionality and performance targets. 

Outcome: A clear migration strategy and defined success criteria. 

STEP 4:
Plan, Execute & Validate Migration

Objective: Plan, perform, and validate the migration, ensuring data integrity and performance standards.

Action: Assign tasks, run Yellowbrick in parallel, and validate data consistency and performance under all conditions.

Outcome: Migration is executed, with successful data validation and performance targets met.

Transform data into action

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