Data Culture

Data Culture

Data Culture

Data culture is Decision culture
Why democratization of data is important

Why
democratization
of data is important

grass-roots

Data is exciting for people at any level in the organization, but only if it is built up from the grass-roots – not imposed top-down, and which promises some competitive advantage.

organizational structure.

Not doing so makes analytics capabilities isolated from the business, resulting in an ineffective analytics organizational structure.

analytics initiatives embed analytics

It’s been observed that organizations with successful analytics initiatives embed analytics capabilities into their core businesses. If these initiatives are centralized or in sporadic pockets, the organization will struggle to create value, and the initiatives are largely perceived to be ineffective.

decentralization

On the flip side, complete decentralization creates data models that don’t connect.

decision-making

Decision makers need to keep an ear to the ground for complaints from Data Science teams that their work is largely being ignored or not factoring sufficiently in decision-making.

democratize data-analytics

It’s crucial to figure out how to really democratize data-analytics capability. Data has to flow across the organization seamlessly.

Bundled with Granular Data, BrandIdea is the only Analytical Platform in India that can give your teams quick access to relevant data. Sales & Marketing teams would start believing their decisions based on data and start delivering solutions that don’t require an expensive data scientist. When teams have access to relevant data for their daily work, it results in bursts of energy & a gush of oxygen in the Organization. There would be a new found realisation on what is possible and the innovation that’s possible. Because the right data applied to the right business problem, creates innovation.

Data culture is Decision culture

During times of crisis, having greater visibility and granularity into your analytics strategy becomes that much more important.

Data should be for a purpose—not the purpose.

If you’re looking to enhance your #dataculture and empower your analysts to drive those life-saving decisions, let’s talk.

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