Insights Blog

How to build a data culture by creating an analytics community: part 1

Blog snapshot:

In this post, we’ll take you through:

  • The benefits of building a data and analytics community 
  • Why this is now more important than ever
  • The key attributes of a strong community

Do you want your organization to be ‘data driven’? Do you want your people to see and understand the value of data and use it in their daily work to produce better outcomes? What does being data-driven even mean to you?

Creating a data-centric culture in your business will not happen overnight because it requires a shift in mindset. It is, however, a goal that becomes more attainable when not dictated from the top but when your people work towards it with passion and enthusiasm. This is where communities play such a vital role.

Why there’s no better time to build a community

The current crisis caused by the global COVID-19 pandemic has shaken many of us to the core and turned our lives upside down. It has caused disruption, uncertainty and major change. And as many of us adjust to these new circumstances, we see innovation and ideas give rise to new ways of collaborating and of working together across physical distances.

There are many communities that operate virtually already, especially around data and analytics. Platforms like GitHub and Kaggle engage people around a variety of topics and give them the tools to collaborate.

There are virtual meetups and communities around Loading...data science, data analysis and visualization.

We can take inspiration from these communities and apply some of their approaches to our own organizations to establish internal analytics communities.

What’s the benefit?

Bringing together your data professionals in a community within your own organization allows them to work collaboratively on solving analytical problems, to find better ways to address business questions and to optimize data engineering processes.

It also provides an opportunity to create informal internal training structures through which you can increase data literacy across your business. Connecting those who are new to data analysis with experienced data analysts creates teaching and learning situations that connect directly to your organization’s data, business processes and current data challenges.

The secrets of a strong community

I have worked in and with a number of different analytics communities over the past few years and they have some characteristics in common:

  • Members have a shared interest for example in data engineering, Loading...data science, data analysis, or Loading...data visualization. This is what brings them together in the first place.
  • The communities are initiated and driven by passionate people who are keen to create an environment where everyone can contribute their unique skills and talents.
  • There is a strong emphasis on knowledge exchange, learning and applying new skills, as well as networking. This helps organizations break down silos, benefit from collaboration and share resources across departments and geographical boundaries.
  • The communities become a place for innovation, trial and error and establishing best practices. Members can test hypotheses and discuss them with others who are working on similar problems. Through collaboration new ideas can emerge and the community, with its expertise and experience, is a great place for collecting and sharing best practices.

What’s next?

How can you set up an internal analytics community in your organization? I have developed a simple four-pillar framework for getting started, which I will share in my next article, so keep an eye on this blog for more.

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