Approaching its IPO, a leading technology unicorn was challenged with limited trust in data accuracy, eroding the ability of leaders to confidently characterize the performance of the business. As a consequence of rapid growth to global scale, internal data systems grew up in siloes, aligned with the different functional areas of the business, with no centralized data governance process or data architecture.

The lack of governance in the company’s data model allowed anyone in the business to instantiate or redefine key metrics, but this meant it lacked a clear audit trail to track adherence to standard business definitions, evolution of metrics over time, and computational efficiency and accuracy. They needed to be able to manage and communicate their business performance with clear confidence and limited manual effort—this required data clean-up, metric certification, and the establishment of repeatable processes and scalable architecture.

With Accenture’s help, this company has rearchitected its data pipelines using a fully relational, as-a-service Snowflake data warehouse with a robust data governance organization on top. Snowflake provided the ability to scale up and down, automatically and on the fly, providing the exact performance needed, at the time needed.

It all sounds really simple, but it is not that simple when it comes to us…We basically went and looked at what the "main" KPIs are and how they are calculated. That’s where Accenture was really helpful!

Strategy and solution

With an IPO making company performance data even more important, everyone at this leading unicorn knew a rethink of internal data management was called for.

Recognizing the time and effort involved in putting its own team together, the company asked Accenture to help it take data management to the next level. The vision? To build a flexible, fast, future-ready data architecture and compliment it with a far more mature approach to data governance. Accenture got to work straight away, putting a small team of focused experts on the ground with an initial goal of helping the company map the lineage of all its existing data and metrics.

The team conducted detailed interviews with data owners and gathered intelligence from other stakeholders to establish the true “as is” state of the company’s data management.

By pulling all the data from the data lake and putting it into a new data store, the team were able to radically simplify and streamline the reporting and make the ad hoc analysis far faster.

Choosing Snowflake meant the ability to perform simultaneous data loading and computation, a feature not found in any other data warehouse solution and a significant boost for productivity and efficiency.

The team also developed a set of recommendations for a mature data management model, including data hygiene factors and a data governance board.

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Within a year, the company’s metrics had been upgraded and a robust data management structure had been created. The result was a dramatic boost in the company’s confidence in its own data, especially as it approached its IPO.

Sleek and user-friendly data dashboards

Everyone across the business can now access intuitive and simple-to-use visualizations of key company data instantly.

Deeper insights from drill-down capabilities

The new solution allows users to slice and dice any combination of top-line figures and compare the results by geography, time period, or other parameters.

Daily business insights

The solution’s speed and simplicity is saving hundreds of analyst hours yearly.

Ability to scale metrics at the point of need

Users now have access to simple “drag and drop” functionality for creating new metrics.

Mature data management

With changes to data and metrics tracked by a data governance board, no arbitrary or undocumented modifications are made to complex data queries.

Foundation for intelligent operations

The business has an industrialized data platform for exploring machine learning and automation, opening up possibilities for insights and performance gains.

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