Information Analytics: Embracing Information Anarchy

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In today’s world of plentiful analytics capability, embracing information anarchy would sound a complete anathema to most people. But the problem is that planning strategic data warehousing and dashboarding solutions often involve many stakeholders and can take several months to design and complete. While that remains a commendable longer-term approach to information analytics, there is a lot you can do tactically in the meantime, often with tools commonly at your disposal.

Dashboarding projects are typically driven by pressing business needs. You need the information now and waiting months for the strategic data warehousing project to be fully scoped, adequately resourced and implemented before seeing the metrics, is simply unacceptable. 

So, with that as the background to the problem, what can you do today to get nearer to your ultimate objective?

Well, the perceived anarchy of the spreadsheet (as with other informal data sources) perhaps has more to do with underlying data governance, data ownership and collation process issues than with the tools and sources themselves. In the interim, follow this method for information analytics.

Proof the Data 

For any such data-driven initiative, start by thinking about who is providing the data, how it is being generated, when it is produced and what it is supposed to represent. Getting clarity on these basics is essential to building a model that will be accepted. 

Assign Ownership of Data & Implement SLAs

Then, armed with this information and sooner rather than later, processes and controls should be implemented, to assign ownership of data and execute SLAs (service level agreements, or in other words, the timing of when verified data is published). SLAs are crucial for monitoring and strengthening the validity and hence integrity of the data produced. 

Essentially this provides you with the necessary support framework to iteratively improve your data-driven application throughout its expected lifetime. 

Imagine that – an environment where consumers are actively encouraged to suggest improvements and refinements rather than merely accepting the status quo. 

You may not get it entirely right from the outset, so by soliciting feedback; you promote a philosophy of collaboration and improvement. Working together is more helpful than encouraging disaffected participants to quickly revert to their own personal, siloed view of the data and all the conflicts that come with it.

Use Informal Data in the Interim 

On this journey of information analytics, informal data can be perfectly viable as an interim data source. At the same time, the more permanent, dynamic connections to underlying business systems are developed to feed the data warehouse. 

These tactical solutions can begin to address the pressing business need, often meeting 80% or more of requirements in a useful time frame. Sometimes you have to work fast to lay the track while the train is already in motion.

It is unlikely that this tactical approach to reporting and analytics becomes wasted effort; more likely is that it ends up informing the strategic data warehousing initiatives and project. And highly likely will prevent it from becoming derailed by spurious tactical scope changes along the way.

Build Reports & Dashboards with BI Tools

Reports and dashboards can now be built on top of the interim data sources by connecting any of the BI tools commonly available, such as Microsoft Power BI, Qlik and Tableau. 

These BI tools are capable of integrating multiple sources into a reliable data model for further analysis. You then have a single, common view of the data that the whole business can work with.

The BI tools available today all support multiple, disparate data sources. They all support code and model refactoring. They all offer similar mainstream utility while specialising in their own corner cases. 

As a result, there is absolutely no reason for you to make a purchasing decision at the outset of an analytics initiative. Instead, use the development journey to evaluate candidate products as part of the long-term BI strategy.

Having a sound process and governance framework in place will allow you to refactor data sources, migrate between different products and most importantly, embrace information anarchy.

At Salient, our data analytics team can help you unlock the secrets your data holds, ensuring accurate information gets to the appropriate people at the right time to facilitate insightful and actionable decisions in line with your business objectives. For your information analytics requirements, get in touch with us today. 

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