For many enterprise users I speak with, the future of analytics seems uncertain and rather cloudy. They have invested in self-service business intelligence and visualization, but they’re not sure if that’s enough to stay ahead of their business needs in the future. They wonder about new technologies like data science and machine learning and worry how to keep up with the pace of development and innovation. And they understand that while they have more data than ever (and that’s a good thing) they also know that they’re analyzing only a fraction of all the information that flows through their organization.
Donald Farmer, Principal, TreeHive Strategy
Donald will be speaking at the IRM UK Data Governance Conference & Master Data Management Summit Europe 12-15 May 2020, London
He will be presenting the keynote, ‘The Culture of Governance‘ and he will be presenting the post-conference workshop, ‘Governance and Compliance in the Age of Self-Service‘
I think it’s true that the new world of data has left traditional BI behind. At the least, reports and dashboards built over well-structured shared data sources are now simply a commodity. New insights and new value will come from more complex data such as natural language and from more advanced analytic technology such as machine learning. But we also need more action.
For me, data without analytics is a wasted asset, but analytics without action is a wasted effort. We need a better approach to information strategy: one which includes real-world data, useful insights and effective actions.
The language of analytics – the analytics of language
One promising area is the use of natural language. It’s possible now to generate telling narratives from visualizations, reports and dashboards. This helps users who are not specialists to understand trends and patterns that they might not otherwise see. Narratives can also help with communication and collaboration when we want to take action on one the business insights we have gleaned from our data.
We can also use natural language as an input. For example, natural language query tools are, in effect, very familiar with if we work with tools like Siri or Alexa. Similar technology can be applied to database sources to make it much easier for business users to interact with business information.
It’s also very important to recognize that natural language data sources such as email, and even the comments fields in your CRM records, contain vital business information that can in turn be analyzed.
For these reasons I often advocate natural language technologies to clients who struggle with how to make new insights available to a wider audience within their organization.
The unfamiliar familiar
If we do want to reach a wider audience, there is of course one tool which we all know well – the spreadsheet. We might think of the spreadsheet as a very light weight tool, but in fact many people do quite complex analysis right there with the simple grid of numbers, text and formulas.
Today we can see spreadsheet technology advancing in new directions. Spreadsheet extensions can handle huge volumes of data. Data science add-ins enable considerable complexity. For me, even more interesting to the regular spreadsheet users, is the ability to use your workbook as a no-code platform for building mobile apps and web interfaces. With these tools, data can be consumed more easily and even business users can build quite advanced experiences and workflows.
A new path
For all these reasons, I’m excited about the future of analytics, business intelligence and data within organizations, but I do recognize that we have to think more carefully about how we advance and promote new technologies. We are at a phase where new developments can seem confusing. By leveraging familiar experiences such as natural language and the power of spreadsheets we can build a more focussed analytic culture, while enabling business users to step into the future with more confidence.
Donald Farmer is an internationally respected speaker and writer, with over 30 years’ experience in data management and analytics. His background is very diverse, having applied data analysis techniques in scenarios ranging from fish-farming to archaeology. He worked in award-winning start-ups in the UK and Iceland and spent 15 years at Microsoft and at Qlik leading teams designing and developing new enterprise capabilities in data integration, data mining, self-service analytics, and visualisation. Donald is an advisor to globally diverse academic boards, government agencies, and investment funds and also advises several start-ups worldwide on data and innovation strategy.
Copyright Donald Farmer, Principal, TreeHive Strategy