Bad Data is Bad for Business
Many studios, especially when young, struggle to understand their data deviations. They’re the lucky ones. Other studios don’t know their data is inaccurate until too late.
Bad data isn’t willful. It exists because something formed it, something else failed to validate it, and something else broadcast it.
Dive helps studios avoid systemic problems raised by poor quality data. Clients
get very high confidence in the integrity of the data they use to make important
We carefully ingest, validate, and surface game data intelligence for
reliable growth expectations.
We’ve learned a thing or two in the 20 years we’ve been in the game industry.
Game studios will starve in the absence of good game data – and a lot of it.
A single player can generate hundreds of events per session. Translating insight from the actions of hundreds of players is a challenge few game studios can accomplish on their own – nor should they.
Game developers are not data engineers.
Data engineering - not to be confused with data analytics or data science - is one of the most important aspects of the business. It is also the one thing a studio should not do for itself, at least not until it’s big enough to hire its own dedicated team.
Data analysts are not data engineers.
Data science is the process of putting data to work; it uses models to identify business opportunities and to act on it. Data science is a decision-making solution that depends on the integrity, the truthfulness, of data.
Data engineering assumes responsibility for truthfulness
This is done via a discrete process to collect, validate, and publish quality data. The quality – and quantity – of available data is as important as its analysis; the value of each is directly dependent on the value of the other.