Technology is helping enterprise data leaders break down analytics silos and empower staff to analyze data without compromising on data governance
Lack of trust in data will undermine any story a company’s data and analytics professionals tell with it. If company decision-makers don’t trust the data that underpins analytics insights or visualizations, they may be inclined to ignore the stats and ‘go with their guts’.
Ensuring data is well-governed and high-quality is the best way to ensure people trust it. But when someone downloads a dataset onto their own device to analyze it, they create an ungoverned analytics silo the data team can’t manage or govern effectively.
This ‘insight generation dilemma’ has hampered data-driven decision-making in enterprise settings for decades.
“It’s a problem that’s been around for a long time,” notes James Calvert, Chief Data Strategy Officer at M&C Saatchi London. “But it takes a grownup organization to invest in that, because that takes time and effort to put in place. And you’re putting it ahead of any of those insights.”
Luckily, this dilemma can be solved. In fact, a growing number of European organizations are implementing modern BI solutions that enable teams to uncover valuable insights without compromising on data governance or undermining trust in the data.
Research from Dataversity shows that roughly two thirds of enterprises have now deployed data preparation, data governance or data intelligence solutions to create a foundation of trusted data within their organizations.
It All Starts with a Single Source of Truth
‘Single source of truth’ (SSOT) is one of the most ubiquitous phrases in the data and analytics industry. It’s a simple idea that we all should live by: If everyone draws their data from the same trusted sources, then everyone will know the data can be trusted.
Establishing a SSOT for data also helps companies ensure data is used in a way that complies with regulations around respecting customer privacy and handling personal data securely.
For these reasons, IAG Loyalty CDO Kinnari Ladha has made establishing a SSOT for data one of her first priorities since joining the company in November 2020.
“We’re really focusing on centralizing the data,” she says. “We’re trying to get a single source of the truth by aligning data sources, to build trust in any analytics we build.”
Enterprises with more mature data functions already have the right data infrastructure in place to ensure data can be managed centrally and provide staff with access to the datasets they need for analytics projects.
At this point, the priority becomes educating stakeholders about why working in this way is so important.
“[It’s] getting across to everybody that a trusted single source of data is not just what’s desirable, it’s actually essential. We’ve made a huge amount of progress towards that”Eddie Short, CDAO and Director, Data, Insights and Analytics, Telefonica UK
“One of our key achievements [for 2020], was getting across to everybody that a trusted single source of data is not just what’s desirable, it’s actually essential,” says Eddie Short, CDAO and Director, Data, Insights and Analytics, Telefonica UK.
“We’ve made a huge amount of progress towards that,” he continues. “So, people can do their own analytics. They can put their own Excel models together, providing they’re doing it from the same data.”
Securing buy-in for working in this way has had a real impact on trust in data at Telefonica UK. For example, it means executives know they’re all using the same data source data when presenting figures at board meetings.
Of course, the benefits of working in this way are clear. The real challenge is ensuring staff can find, access and analyze the data they need to generate valuable insights quickly and easily.
Empowering Staff to Deliver Trusted Analytics
Ensuring the data a company’s staff use to generate insights is drawn from trusted sources is as much about having good processes and promoting good analytics practices as it is about curating trusted datasets.
At IAG, Ladha wants staff to move away from desktop-based tools such as Excel and build their dashboards on top of a centralized data platform.
“One of the biggest values of this group data platform is to centralize the data, but also to start utilizing modern analytics tools,” she says.
“[Today], we do have a lot of dashboards in Excel, but we need to move away from that,” she adds. “That worries me, because I don’t know what formulas sit behind there!”
Telefonica UK is taking a slightly different approach. There is a wide range of legacy systems and BI tools in use across the company. So, Short is focusing his efforts on consolidating this into a selection of modern analytics platforms and ensuring everyone works from the SSOT.
“It’s more a question of effectively having [approved] dashboards, so that things that go to the primary executive meetings have been signed off as coming from the trusted source of data,” he says. “That’s the key thing.”
“I think that that those who invest in data governance will do better, and I hope that brands do continue to do that”James Calvert, Chief Data Strategy Officer at M&C Saatchi London
This pragmatic approach may be the way to go for legacy organizations. But is does make it trickier to govern who gets access to analytics models and their underlying data after they have been created.
Either way, technology providers are also working to make their platforms interoperable with other solutions to facilitate these transformations.
“We’re providing access into our platform for third-party tools,” says Pyramid Analytics Principal Technologist Ian Macdonald.
“The other thing we’re doing is opening up what we call the semantic model,” he adds. “That means, if I build an analysis in the Pyramid platform, for example, that particular analysis is accessible to other tools.”
Analytics ecosystems with this kind of interoperability help staff to tell stories with data using their preferred tools without creating ungoverned silos. In doing so, they help to promote trust in analytics insights and enable analytics innovation in a way that’s consistent with good data governance.