CAPABILITY 01
Data pipelines & ETL/ELT
Batch and incremental pipelines that ingest from databases, files, APIs, and SaaS systems — with error handling, retries, and lineage.
ETL / ELTAWS GluePythonAirflow
Home / Capabilities / Data Engineering & Analytics
Data to decisions
Data Engineering & Analytics
Trusted data, delivered to the people who decide.
SIS designs and validates the pipelines, warehouses, and dashboards that turn scattered records into reliable, governed insight — with data quality checks at every hop.
Data pipelines & ETL/ELTData warehousingLakehouse & big dataData quality & reconciliation
Overview
Trusted data, delivered to the people who decide.
Analytics is only as good as the data underneath it. SIS combines data engineering with a testing mindset: pipelines are built to be observable, data is reconciled against its source, and every metric has a definition someone can find.
We help organizations modernize from spreadsheets and siloed databases to cloud warehouses and lakehouses, then put that data to work in dashboards, analysis, and predictive models.
Focus areas
- Data pipelines & ETL/ELT
- Data warehousing
- Lakehouse & big data
- Data quality & reconciliation
- Data governance & cataloging
- Master & reference data
What's possible
Capabilities across data engineering & analytics.
The technical areas SIS can support, and what each makes possible for your mission.
CAPABILITY 02
Data warehousing
Dimensional and analytics-ready models on cloud warehouses, with performance tuning, partitioning, and cost awareness.
Amazon RedshiftSnowflakeStar schemaSQL tuning
CAPABILITY 03
Lakehouse & big data
Open-format data lakes for large or semi-structured data with query engines on top, separating cheap storage from compute.
AWS S3Parquet / IcebergSparkAthena
CAPABILITY 04
Data quality & reconciliation
Automated checks for completeness, validity, duplicates, and source-to-target reconciliation — the same rigor we apply in IV&V.
Data quality rulesReconciliationGreat ExpectationsAlerting
CAPABILITY 05
Data governance & cataloging
Data dictionaries, ownership, classification, lineage, and access policies so data is discoverable and protected.
Data catalogLineageClassificationStewardship
CAPABILITY 06
Master & reference data
Golden records for people, assets, and locations; deduplication and matching across systems.
MDMEntity resolutionReference dataMatching
CAPABILITY 07
Business intelligence & dashboards
Executive and operational dashboards with clear metric definitions, drill-downs, and role-based access.
Power BITableauQuickSightKPI design
CAPABILITY 08
Statistical & predictive analytics
Trend analysis, forecasting, segmentation, and what-if modeling that inform budget, staffing, and program decisions.
PythonRForecastingStatistical testing
CAPABILITY 09
Real-time & streaming data
Event streams for near-real-time monitoring, alerting, and operational dashboards.
KinesisKafkaEvent processingStream analytics
CAPABILITY 10
Geospatial analytics
Mapping and spatial analysis of assets, incidents, and field data — including imagery and drone-collected data.
GISPostGISSpatial joinsMap dashboards
Mission applications
Where it makes a difference.
Representative ways organizations put these capabilities to work.
Program performance dashboards
One trusted view of KPIs for leadership and oversight reporting.
Legacy data modernization
Move from on-prem databases and spreadsheets to a governed cloud warehouse.
Data migration validation
Prove migrated data is complete and correct before go-live.
Evidence-based policy
Combine program, financial, and survey data to measure outcomes.
Operational alerting
Detect late, missing, or anomalous data before it misleads decisions.
Self-service analytics
Give analysts governed, documented datasets instead of ad-hoc extracts.
Our approach
A disciplined path from need to outcome.
- 01
Discover
Inventory sources, consumers, definitions, and pain points.
- 02
Model
Design the target data model and the metrics that matter.
- 03
Build
Implement pipelines with tests, monitoring, and lineage.
- 04
Validate
Reconcile against source systems and sign off with data owners.
- 05
Enable
Deliver dashboards, documentation, and training for self-service.
Tools & technologies
Technology we work with.
We are tool-agnostic and start from what you already use. Representative technologies:
Storage & warehouse
Amazon RedshiftAWS S3PostgreSQLOracleSQL Server
Processing
SQLPython / PandasSparkAWS GlueAirflow
Visualization
Power BITableauAmazon QuickSightExcel
Quality & governance
Data quality rulesData catalogsLineage toolingAccess controls
Standards & frameworks
Aligned to the guidance that matters.
- Federal Data Strategy principles
- Evidence Act data practices
- NIST SP 800-53 data protection controls
- PII and privacy handling requirements
- Section 508 accessible dashboards
Questions
Frequently asked.
Can you work with our existing tools?
Yes. We are tool-agnostic and start from what you already license and support, recommending changes only when they clearly pay off.
How do you ensure the numbers are right?
Automated data-quality checks and source-to-target reconciliation are built into the pipeline, and metric definitions are documented and agreed with data owners.
Do we have to move everything to the cloud?
No. Hybrid patterns are common; we help decide what moves, when, and why.
Can dashboards be accessible?
Yes — we design dashboards with Section 508 considerations such as color contrast, keyboard navigation, and data-table alternatives.
Related capabilities
Works well with.
AI
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Let's explore the mission requirements.
Connect with SIS to discuss technical needs, collaboration, or teaming opportunities.