Data literacy: more than training

This is a guest blogpost by Adrian Seow, head of product marketing, Yellowfin

In the era of self-service analytics, data literacy is an increasing priority, but helping people understand their data better requires more than just training.

In many enterprise circles, helping more business users become fully data literate is often considered a challenge that can only be met with organisation-wide cultural change and training.

However, while taking this approach is well intended, approaching data literacy as a standardised program can lead to potential overtraining, and put undue strain on chief data officers (CDOs).

The fact is the way business professionals explore, consume and analyze information, and their unique use cases for analytics, will always be different depending on role, industry, and workflow.

A line-of-business user, for example, may only need to consume an overview (dashboard) of performance to find answers, and will not need the same level of training to understand it as a data scientist, who prepares, analyzes and presents more complex business data for a living.

Many employees only need a basic level of data literacy to do their job well and putting them through the same enterprise-grade literacy programs as data experts could be time and resources spent elsewhere, such as showing them how they can better use data within their workflow, rather than a technical breakdown of how to extract reports out of their software.

Instead, to better meet the varying literacy requirements across the organization, CDOs should more closely examine business intelligence (BI) software vendors, and how the tools themselves can offer users the exact capability they need, without requiring extensive training.

Tailoring data literacy for the role, and competency, required

Modern enterprise BI solutions are no longer the sole domain of trained data experts. Today’s platforms are increasingly designed in a way non-technical professionals can use analytical capabilities to explore data, find actionable insights and extract meaning, faster and easier.

Instead of introducing more data tools to be trained in, many analytics vendors are lessening the need for advanced literacy for users to get in and start exploring and finding meaning from data.

How?

Some vendors make this possible through the infusion of powerful technologies such as augmented analytics (AI and machine learning), automation, data storytelling, and natural language, which do most of the heavy lifting of preparing and interpreting it for the user.

These are then offered as streamlined features, such as automated alerting, and are scalable depending on the user’s needs. A non-technical user, for example, can quickly set up automated alerts for when a trend in data changes in their dashboards without extensive training, while a data expert can leverage the same feature in more advanced ways, should they choose to, as the BI platform has built that capability with the various different levels of data literacy in mind.

With such advancements more readily available as streamlined tools, it’s more important than ever for the CDO and organisational leadership to examine their options in the BI space, and select and demand capabilities from their chosen vendor that help their users better understand data and how to use it, without the previously high technical ceiling to actually use said tools.

If you’re still using a BI platform that requires more time training users to know how to consume the data within, now is the right time to begin exploring what other options may better suit.

Only what they need to know

Ultimately, businesses will have employees that have very different data needs, and different use cases for BI software. Finding the right analytics vendor that can cater to this is more effective than attempting to create one standardised data literacy training programme.

Data scientists that need access to advanced data preparation techniques, for example, will need comprehensive training, but regular business users, such as marketing managers, shouldn’t need to be experts in this area, nor should they be expected to be, to consume data relevant to their workflow. They should only need to know enough, and have enough capability at their disposal, to be an expert in their domain.

By paying more attention to the many modern BI software options available that tailor their tools to users of all skill levels, roles and sectors, enterprises will be better capable of increasing data literacy throughout the business, where the training and knowledge is required the most.

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