The Sea of SaaS can be a Dangerous Place

Unify data across SaaS applications & Accelerate your time to analytics

Avoid the Whirlpool of Data Chaos

whirlpool

Once, a man practiced the ancient rite of Data Prep. He built ETL routines by hand. The data prep was endless.

Every day he fished the Sea of SaaS for answers, hugging the shore of his API limits.

But soon he grew worried by his small catch, and steered, unwittingly, into Data Chaos.

Discovering the City of Fusion

In the City of Fusion, he discovered all records, from multiple databases, matched by object & system. Duplicates had vanished, & formats standardized. From many systems shone a unified dataset of fused records, related by a single schema.

city of fusion

In his Fused Database were fused, raw, & links tables. Fused combined all major objects, like activities & company, across his systems. Raw put all his system’s major objects in one database rather than many. And the links tables were like mythical wizards, whose wands helped him join & query in ways he’d always wanted, but never imagined.

treasureChest

His warehouse wended into any analytics tool with a MySQL connection. To change his object mappings, he just dragged & dropped & Fusion built a fresh warehouse, with data updating every 30 minutes.

octopus

Surely this was a dream. For every object - from Accounts & Opportunities to Activities & Campaigns - had been mapped. Many data models had been transformed into one schema, automatically updated and maintained for him.

treasureMap

Arriving to Insight Island

On land, he tinkered yet again, this time in tools like Amazon Quicksight, Power BI, Tableau, Looker, Metabase, Yellowfin, Qlik, & more. With SQL he queried data in real-time, with a daily view of KPIs on a single dashboard.

radar

Around the watercooler, coworkers heard his tale. How more than time was saved, more than money made.

And his village — of CRM admins, marketing, customer operations, IT, & analysts — also felt more confident. Heroic. The ancient rite of Data Prep had been slain, as had the limits of what they could now discover in their SaaS data.

lounging
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