Turn 20 Hours of Data Engineering into one Click
Turn 20 Hours of Data Engineering into one Click
DataGOL's innovative orchestration engine makes as-of reporting effortless. No more manual queries, no more engineering bottlenecks.
DataGOL's innovative orchestration engine makes as-of reporting effortless. No more manual queries, no more engineering bottlenecks.
1-Click
Historical reporting
Zero
SQL Required
Zero
SQL Required
Zero
SQL Required
Read the Case Study
Read the Case Study
The Hidden Cost of "As-Of" Reporting
Every time your business needs historical data insights, your data engineering team drops everything to manually extract snapshots and refresh dashboards.
The Problem
Orchestrated Time-Travel
Manual Querying Nightmare
Each as-of request requires manually inputting date parameters across multiple queries in Databricks or Snowflake
One-Parameter Orchestration
Set a single AS_OF_DATE parameter and watch it flow through your entire data pipeline automatically
One-Parameter Orchestration
Set a single AS_OF_DATE parameter and watch it flow through your entire data pipeline automatically
One-Parameter Orchestration
Set a single AS_OF_DATE parameter and watch it flow through your entire data pipeline automatically
Broken Data Lineage When you rollback one table, downstream dependencies don't automatically update, creating inconsistent data
Broken Data Lineage When you rollback one table, downstream dependencies don't automatically update, creating inconsistent data states
Dynamic BI Dashboard Versioning Your Power BI and Tableau dashboards automatically generate versioned views
Engineering Bottleneck
Business users can't self-serve historical insights. Every request goes through your already-overwhelmed data team
Engineering Bottleneck Business users can't self-serve historical insights. Every request goes through your already-overwhelmed data team
Automated Pipeline Consistency
When you time-travel one data source, all dependent tables automatically rollback to maintain data integrity
Automated Pipeline Consistency
When you time-travel one data source, all dependent tables automatically rollback to maintain data integrity
"DataGOL turned our data warehouse into a time machine. We stopped asking engineers for historical reports and started answering questions ourselves."
VP of Data, PE backed SaaS Company
What Makes DataGOL Different
The platform that transformed Remo's analysts from data bottlenecks to insight heroes.
Automation
Run parameterized orchestration with AS_OF_DATE
Run parameterized orchestration with AS_OF_DATE
Reduces manual data ops by 65%
Enterprise-
grade security
Enterprise-
grade security
Built-in compliance and security standards
Uses existing document like Manuals, Policy's, FAQ's to respond to Customers internally or externally.
Unified platform
Automation
Eliminates tool sprawl and vendor management complexity
Run parameterized orchestration with AS_OF_DATE
Eliminates tool sprawl and vendor management complexity
Unified platform
Eliminates tool sprawl and vendor management
87% Ticket Reduction
87% Ticket Reduction
Self-serve analytics reduces engineering tickets by 87%
Stop Burning Engineering Hours on Repetitive Queries
See how DataGOL can eliminate your as-of reporting bottlenecks in a 15-minute demo
No commitment required • See results in 15 minutes • Works with your existing Snowflake/Databricks
Your Analysts Shouldn't Be Data Bottlenecks
Remo's analysts were facing the same challenges plaguing data teams everywhere.
The Problem
DataGOL: Orchestrated Time-Travel
Manual Querying Nightmare Each as-of request requires manually inputting date parameters across multiple queries in Databricks or Snowflake
One-Parameter Orchestration
Set a single AS_OF_DATE parameter and watch it flow through your entire data pipeline automatically
Broken Data Lineage When you rollback one table, downstream dependencies don't automatically update, creating inconsistent data states
Dynamic BI Dashboard Versioning Your Power BI and Tableau dashboards automatically generate versioned views
Engineering Bottleneck Business users can't self-serve historical insights. Every request goes through your already-overwhelmed data team
Automated Pipeline Consistency When you time-travel one data source, all dependent tables automatically rollback to maintain data integrity