A Global Media Transformation from BI Bottlenecks to Scalable Insights

$5,000+

7-12 months

Australia

2-5

Service categories

Service Lines

Big Data

Domain focus

Media & Entertainment

Challenge

Managing Rapidly Growing Datasets: The company had to deal with data coming in from many different places at an ever-increasing rate, which put a lot of stress on the current infrastructure.
DOMO's Scalability Problems: The current DOMO solution had performance problems that made it hard to scale and meet business needs.
Slow Data Retrieval: With cloud-based processing in DOMO, data queries took a long time and decision-making was less efficient.
Need for Large-Scale Migration: More than 150 dashboards had to be moved from DOMO to Tableau without affecting business as usual.
Complex Dashboard Adaptation: The designs and calculations on DOMO dashboards were very complicated, so they had to be carefully changed to work in Tableau.

Managing Rapidly Growing Datasets: The company had to deal with data coming in from many different places at an ever-increasing rate, which put a lot of stress on the current infrastructure.
DOMO's Scalability Problems: The current DOMO solution had performance problems that made it hard to scale and meet business needs.
Slow Data Retrieval: With cloud-based processing in DOMO, data queries took a long time and decision-making was less efficient.
Need for Large-Scale Migration: More than 150 dashboards had to be moved from DOMO to Tableau without affecting business as usual.
Complex Dashboard Adaptation: The designs and calculations on DOMO dashboards were very complicated, so they had to be carefully changed to work in Tableau.

Phased Migration Strategy: We used a step-by-step plan for migration, with five teams working together to make sure everything went smoothly.
Using Tableau for Scalability: We switched to Tableau because it can handle and show large datasets quickly and easily.
Centralized Data Warehouse with Snowflake: We combined more than 550 different datasets into Snowflake, which gives us one reliable source of truth for analytics.
Optimized Tableau Dashboard Design: Redesigned and improved dashboards and calculations in Tableau to get the same results as DOMO while making them work better.
Strategic Deployment Approach: For smaller datasets, we used incremental refresh to speed up load times, and for larger datasets, we used live connections to keep insights up to date.

Phased Migration Strategy: We used a step-by-step plan for migration, with five teams working together to make sure everything went smoothly.
Using Tableau for Scalability: We switched to Tableau because it can handle and show large datasets quickly and easily.
Centralized Data Warehouse with Snowflake: We combined more than 550 different datasets into Snowflake, which gives us one reliable source of truth for analytics.
Optimized Tableau Dashboard Design: Redesigned and improved dashboards and calculations in Tableau to get the same results as DOMO while making them work better.
Strategic Deployment Approach: For smaller datasets, we used incremental refresh to speed up load times, and for larger datasets, we used live connections to keep insights up to date.

Big Drop in Computing Time: By using incremental refresh for smaller datasets, we were able to cut overall computing time by 80%.
Faster Query Processing: We cut the time it took to process queries by 60%, which made it easier to get insights and made things run more smoothly.
Better Dashboard Performance: Dashboard visual load times went up by 200–300%, which made the user experience smoother and decisions faster.

Big Drop in Computing Time: By using incremental refresh for smaller datasets, we were able to cut overall computing time by 80%.
Faster Query Processing: We cut the time it took to process queries by 60%, which made it easier to get insights and made things run more smoothly.
Better Dashboard Performance: Dashboard visual load times went up by 200–300%, which made the user experience smoother and decisions faster.